[{"oa":1,"acknowledgement":"We thank everyone who helped with fieldwork, snail processing and DNA extractions, particularly Laura Brettell, Mårten Duvetorp, Juan Galindo, Anne-Lise Liabot, Mark Ravinet, Irena Senčić and Zuzanna Zagrodzka. We are also grateful to Edinburgh Genomics for library preparation and sequencing, to Stuart Baird and Mark Ravinet for helpful discussions, and to three anonymous reviewers for their constructive comments. This work was supported by the Natural Environment Research Council (NE/K014021/1), the European Research Council (AdG-693030-BARRIERS), Swedish Research Councils Formas and Vetenskapsrådet through a Linnaeus grant to the Centre for Marine Evolutionary Biology (217-2008-1719), the European Regional Development Fund (POCI-01-0145-FEDER-030628), and the Fundação para a iência e a Tecnologia,\r\nPortugal (PTDC/BIA-EVL/\r\n30628/2017). A.M.W. and R.F. were\r\nfunded by the European Union’s Horizon 2020 research and innovation\r\nprogramme under Marie Skłodowska-Curie\r\ngrant agreements\r\nno. 754411/797747 and no. 706376, respectively.","status":"public","issue":"15","article_type":"original","external_id":{"isi":["000669439700001"],"pmid":["33638231"]},"citation":{"mla":"Westram, Anja M., et al. “Using Replicate Hybrid Zones to Understand the Genomic Basis of Adaptive Divergence.” <i>Molecular Ecology</i>, vol. 30, no. 15, Wiley, 2021, pp. 3797–814, doi:<a href=\"https://doi.org/10.1111/mec.15861\">10.1111/mec.15861</a>.","ista":"Westram AM, Faria R, Johannesson K, Butlin R. 2021. Using replicate hybrid zones to understand the genomic basis of adaptive divergence. Molecular Ecology. 30(15), 3797–3814.","short":"A.M. Westram, R. Faria, K. Johannesson, R. Butlin, Molecular Ecology 30 (2021) 3797–3814.","ama":"Westram AM, Faria R, Johannesson K, Butlin R. Using replicate hybrid zones to understand the genomic basis of adaptive divergence. <i>Molecular Ecology</i>. 2021;30(15):3797-3814. doi:<a href=\"https://doi.org/10.1111/mec.15861\">10.1111/mec.15861</a>","apa":"Westram, A. M., Faria, R., Johannesson, K., &#38; Butlin, R. (2021). Using replicate hybrid zones to understand the genomic basis of adaptive divergence. <i>Molecular Ecology</i>. Wiley. <a href=\"https://doi.org/10.1111/mec.15861\">https://doi.org/10.1111/mec.15861</a>","ieee":"A. M. Westram, R. Faria, K. Johannesson, and R. Butlin, “Using replicate hybrid zones to understand the genomic basis of adaptive divergence,” <i>Molecular Ecology</i>, vol. 30, no. 15. Wiley, pp. 3797–3814, 2021.","chicago":"Westram, Anja M, Rui Faria, Kerstin Johannesson, and Roger Butlin. “Using Replicate Hybrid Zones to Understand the Genomic Basis of Adaptive Divergence.” <i>Molecular Ecology</i>. Wiley, 2021. <a href=\"https://doi.org/10.1111/mec.15861\">https://doi.org/10.1111/mec.15861</a>."},"publication_identifier":{"eissn":["1365-294X"],"issn":["0962-1083"]},"volume":30,"page":"3797-3814","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","type":"journal_article","_id":"10838","year":"2021","has_accepted_license":"1","abstract":[{"lang":"eng","text":"Combining hybrid zone analysis with genomic data is a promising approach to understanding the genomic basis of adaptive divergence. It allows for the identification of genomic regions underlying barriers to gene flow. It also provides insights into spatial patterns of allele frequency change, informing about the interplay between environmental factors, dispersal and selection. However, when only a single hybrid zone is analysed, it is difficult to separate patterns generated by selection from those resulting from chance. Therefore, it is beneficial to look for repeatable patterns across replicate hybrid zones in the same system. We applied this approach to the marine snail Littorina saxatilis, which contains two ecotypes, adapted to wave-exposed rocks vs. high-predation boulder fields. The existence of numerous hybrid zones between ecotypes offered the opportunity to test for the repeatability of genomic architectures and spatial patterns of divergence. We sampled and phenotyped snails from seven replicate hybrid zones on the Swedish west coast and genotyped them for thousands of single nucleotide polymorphisms. Shell shape and size showed parallel clines across all zones. Many genomic regions showing steep clines and/or high differentiation were shared among hybrid zones, consistent with a common evolutionary history and extensive gene flow between zones, and supporting the importance of these regions for divergence. In particular, we found that several large putative inversions contribute to divergence in all locations. Additionally, we found evidence for consistent displacement of clines from the boulder–rock transition. Our results demonstrate patterns of spatial variation that would not be accessible without continuous spatial sampling, a large genomic data set and replicate hybrid zones."}],"publication":"Molecular Ecology","title":"Using replicate hybrid zones to understand the genomic basis of adaptive divergence","department":[{"_id":"BeVi"}],"publisher":"Wiley","date_created":"2022-03-08T11:28:32Z","oa_version":"Published Version","pmid":1,"ddc":["570"],"day":"01","isi":1,"month":"08","language":[{"iso":"eng"}],"intvolume":"        30","file":[{"relation":"main_file","creator":"dernst","access_level":"open_access","content_type":"application/pdf","success":1,"date_created":"2022-03-08T11:31:30Z","file_id":"10839","date_updated":"2022-03-08T11:31:30Z","file_size":1726548,"file_name":"2021_MolecularEcology_Westram.pdf","checksum":"d5611f243ceb63a0e091d6662ebd9cda"}],"publication_status":"published","author":[{"first_name":"Anja M","orcid":"0000-0003-1050-4969","last_name":"Westram","full_name":"Westram, Anja M","id":"3C147470-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Faria","first_name":"Rui","full_name":"Faria, Rui"},{"full_name":"Johannesson, Kerstin","first_name":"Kerstin","last_name":"Johannesson"},{"full_name":"Butlin, Roger","first_name":"Roger","last_name":"Butlin"}],"date_published":"2021-08-01T00:00:00Z","article_processing_charge":"No","date_updated":"2023-09-05T16:02:19Z","doi":"10.1111/mec.15861","keyword":["Genetics","Ecology","Evolution","Behavior and Systematics"],"scopus_import":"1","quality_controlled":"1","file_date_updated":"2022-03-08T11:31:30Z","tmp":{"image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"}},{"citation":{"short":"P. Tomášek, K. Horák, A. Aradhye, B. Bošanský, K. Chatterjee, in:, 30th International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence, 2021, pp. 4182–4189.","mla":"Tomášek, Petr, et al. “Solving Partially Observable Stochastic Shortest-Path Games.” <i>30th International Joint Conference on Artificial Intelligence</i>, International Joint Conferences on Artificial Intelligence, 2021, pp. 4182–89, doi:<a href=\"https://doi.org/10.24963/ijcai.2021/575\">10.24963/ijcai.2021/575</a>.","ista":"Tomášek P, Horák K, Aradhye A, Bošanský B, Chatterjee K. 2021. Solving partially observable stochastic shortest-path games. 30th International Joint Conference on Artificial Intelligence. IJCAI: International Joint Conferences on Artificial Intelligence Organization, 4182–4189.","ama":"Tomášek P, Horák K, Aradhye A, Bošanský B, Chatterjee K. Solving partially observable stochastic shortest-path games. In: <i>30th International Joint Conference on Artificial Intelligence</i>. International Joint Conferences on Artificial Intelligence; 2021:4182-4189. doi:<a href=\"https://doi.org/10.24963/ijcai.2021/575\">10.24963/ijcai.2021/575</a>","apa":"Tomášek, P., Horák, K., Aradhye, A., Bošanský, B., &#38; Chatterjee, K. (2021). Solving partially observable stochastic shortest-path games. In <i>30th International Joint Conference on Artificial Intelligence</i> (pp. 4182–4189). Virtual, Online: International Joint Conferences on Artificial Intelligence. <a href=\"https://doi.org/10.24963/ijcai.2021/575\">https://doi.org/10.24963/ijcai.2021/575</a>","chicago":"Tomášek, Petr, Karel Horák, Aditya Aradhye, Branislav Bošanský, and Krishnendu Chatterjee. “Solving Partially Observable Stochastic Shortest-Path Games.” In <i>30th International Joint Conference on Artificial Intelligence</i>, 4182–89. International Joint Conferences on Artificial Intelligence, 2021. <a href=\"https://doi.org/10.24963/ijcai.2021/575\">https://doi.org/10.24963/ijcai.2021/575</a>.","ieee":"P. Tomášek, K. Horák, A. Aradhye, B. Bošanský, and K. Chatterjee, “Solving partially observable stochastic shortest-path games,” in <i>30th International Joint Conference on Artificial Intelligence</i>, Virtual, Online, 2021, pp. 4182–4189."},"publication_identifier":{"issn":["1045-0823"],"isbn":["9780999241196"]},"status":"public","acknowledgement":"This research was supported by the Czech Science Foundation (no. 19-24384Y), by the OP VVV MEYS funded project CZ.02.1.01/0.0/0.0/16 019/0000765 “Research Center for Informatics”, by the ERC CoG 863818 (ForM-SMArt), and by the Combat Capabilities Development Command Army Research Laboratory and was accomplished under Cooperative\r\nAgreement Number W911NF-13-2-0045 (ARL Cyber Security CRA). The views and conclusions contained in this document are those of the authors and should not be interpreted as\r\nrepresenting the official policies, either expressed or implied, of the Combat Capabilities Development Command Army Research Laboratory or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes not withstanding any copyright notation here on. ","oa":1,"_id":"10847","year":"2021","page":"4182-4189","type":"conference","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","abstract":[{"lang":"eng","text":"We study the two-player zero-sum extension of the partially observable stochastic shortest-path problem where one agent has only partial information about the environment. We formulate this problem as a partially observable stochastic game (POSG): given a set of target states and negative rewards for each transition, the player with imperfect information maximizes the expected undiscounted total reward until a target state is reached. The second player with the perfect information aims for the opposite. We base our formalism on POSGs with one-sided observability (OS-POSGs) and give the following contributions: (1) we introduce a novel heuristic search value iteration algorithm that iteratively solves depth-limited variants of the game, (2) we derive the bound on the depth guaranteeing an arbitrary precision, (3) we propose a novel upper-bound estimation that allows early terminations, and (4) we experimentally evaluate the algorithm on a pursuit-evasion game."}],"oa_version":"Published Version","date_created":"2022-03-13T23:01:47Z","ec_funded":1,"title":"Solving partially observable stochastic shortest-path games","department":[{"_id":"KrCh"}],"publication":"30th International Joint Conference on Artificial Intelligence","publisher":"International Joint Conferences on Artificial Intelligence","project":[{"call_identifier":"H2020","name":"Formal Methods for Stochastic Models: Algorithms and Applications","grant_number":"863818","_id":"0599E47C-7A3F-11EA-A408-12923DDC885E"}],"language":[{"iso":"eng"}],"month":"09","day":"01","main_file_link":[{"url":"https://doi.org/10.24963/ijcai.2021/575","open_access":"1"}],"publication_status":"published","scopus_import":"1","quality_controlled":"1","date_published":"2021-09-01T00:00:00Z","author":[{"full_name":"Tomášek, Petr","last_name":"Tomášek","first_name":"Petr"},{"last_name":"Horák","first_name":"Karel","full_name":"Horák, Karel"},{"last_name":"Aradhye","first_name":"Aditya","full_name":"Aradhye, Aditya"},{"first_name":"Branislav","last_name":"Bošanský","full_name":"Bošanský, Branislav"},{"orcid":"0000-0002-4561-241X","last_name":"Chatterjee","first_name":"Krishnendu","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","full_name":"Chatterjee, Krishnendu"}],"doi":"10.24963/ijcai.2021/575","date_updated":"2025-07-14T09:10:13Z","article_processing_charge":"No","conference":{"name":"IJCAI: International Joint Conferences on Artificial Intelligence Organization","end_date":"2021-08-27","location":"Virtual, Online","start_date":"2021-08-19"}},{"type":"journal_article","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","volume":33,"year":"2021","_id":"10852","external_id":{"arxiv":["1912.12509"],"isi":["000613313200013"]},"article_type":"original","issue":"01","status":"public","oa":1,"acknowledgement":"This work was supported by the European Research Council (ERC) under the Euro-pean Union’s Horizon 2020 research and innovation programme (grant agreementNo. 694227).","publication_identifier":{"eissn":["1793-6659"],"issn":["0129-055X"]},"citation":{"apa":"Seiringer, R. (2021). The polaron at strong coupling. <i>Reviews in Mathematical Physics</i>. World Scientific Publishing. <a href=\"https://doi.org/10.1142/s0129055x20600120\">https://doi.org/10.1142/s0129055x20600120</a>","ieee":"R. Seiringer, “The polaron at strong coupling,” <i>Reviews in Mathematical Physics</i>, vol. 33, no. 01. World Scientific Publishing, 2021.","chicago":"Seiringer, Robert. “The Polaron at Strong Coupling.” <i>Reviews in Mathematical Physics</i>. World Scientific Publishing, 2021. <a href=\"https://doi.org/10.1142/s0129055x20600120\">https://doi.org/10.1142/s0129055x20600120</a>.","mla":"Seiringer, Robert. “The Polaron at Strong Coupling.” <i>Reviews in Mathematical Physics</i>, vol. 33, no. 01, 2060012, World Scientific Publishing, 2021, doi:<a href=\"https://doi.org/10.1142/s0129055x20600120\">10.1142/s0129055x20600120</a>.","ista":"Seiringer R. 2021. The polaron at strong coupling. Reviews in Mathematical Physics. 33(01), 2060012.","short":"R. Seiringer, Reviews in Mathematical Physics 33 (2021).","ama":"Seiringer R. The polaron at strong coupling. <i>Reviews in Mathematical Physics</i>. 2021;33(01). doi:<a href=\"https://doi.org/10.1142/s0129055x20600120\">10.1142/s0129055x20600120</a>"},"publisher":"World Scientific Publishing","title":"The polaron at strong coupling","department":[{"_id":"RoSe"}],"publication":"Reviews in Mathematical Physics","oa_version":"Preprint","date_created":"2022-03-18T08:11:34Z","ec_funded":1,"arxiv":1,"abstract":[{"text":" We review old and new results on the Fröhlich polaron model. The discussion includes the validity of the (classical) Pekar approximation in the strong coupling limit, quantum corrections to this limit, as well as the divergence of the effective polaron mass.","lang":"eng"}],"publication_status":"published","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1912.12509"}],"intvolume":"        33","day":"01","language":[{"iso":"eng"}],"project":[{"call_identifier":"H2020","_id":"25C6DC12-B435-11E9-9278-68D0E5697425","grant_number":"694227","name":"Analysis of quantum many-body systems"}],"month":"02","isi":1,"article_number":"2060012","date_updated":"2023-09-05T16:08:02Z","doi":"10.1142/s0129055x20600120","article_processing_charge":"No","date_published":"2021-02-01T00:00:00Z","author":[{"id":"4AFD0470-F248-11E8-B48F-1D18A9856A87","full_name":"Seiringer, Robert","orcid":"0000-0002-6781-0521","last_name":"Seiringer","first_name":"Robert"}],"quality_controlled":"1","scopus_import":"1","keyword":["Mathematical Physics","Statistical and Nonlinear Physics"]},{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"conference","page":"208-220","year":"2021","_id":"10853","external_id":{"arxiv":["2105.08098"]},"status":"public","oa":1,"publication_identifier":{"isbn":["9781450380706"]},"citation":{"ama":"Fedorov A, Koval N, Alistarh D-A. A scalable concurrent algorithm for dynamic connectivity. In: <i>Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and Architectures</i>. Association for Computing Machinery; 2021:208-220. doi:<a href=\"https://doi.org/10.1145/3409964.3461810\">10.1145/3409964.3461810</a>","mla":"Fedorov, Alexander, et al. “A Scalable Concurrent Algorithm for Dynamic Connectivity.” <i>Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and Architectures</i>, Association for Computing Machinery, 2021, pp. 208–20, doi:<a href=\"https://doi.org/10.1145/3409964.3461810\">10.1145/3409964.3461810</a>.","short":"A. Fedorov, N. Koval, D.-A. Alistarh, in:, Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and Architectures, Association for Computing Machinery, 2021, pp. 208–220.","ista":"Fedorov A, Koval N, Alistarh D-A. 2021. A scalable concurrent algorithm for dynamic connectivity. Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and Architectures. SPAA: Symposium on Parallelism in Algorithms and Architectures, 208–220.","chicago":"Fedorov, Alexander, Nikita Koval, and Dan-Adrian Alistarh. “A Scalable Concurrent Algorithm for Dynamic Connectivity.” In <i>Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and Architectures</i>, 208–20. Association for Computing Machinery, 2021. <a href=\"https://doi.org/10.1145/3409964.3461810\">https://doi.org/10.1145/3409964.3461810</a>.","ieee":"A. Fedorov, N. Koval, and D.-A. Alistarh, “A scalable concurrent algorithm for dynamic connectivity,” in <i>Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and Architectures</i>, Virtual, Online, 2021, pp. 208–220.","apa":"Fedorov, A., Koval, N., &#38; Alistarh, D.-A. (2021). A scalable concurrent algorithm for dynamic connectivity. In <i>Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and Architectures</i> (pp. 208–220). Virtual, Online: Association for Computing Machinery. <a href=\"https://doi.org/10.1145/3409964.3461810\">https://doi.org/10.1145/3409964.3461810</a>"},"publisher":"Association for Computing Machinery","publication":"Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and Architectures","title":"A scalable concurrent algorithm for dynamic connectivity","department":[{"_id":"DaAl"}],"date_created":"2022-03-18T08:21:47Z","oa_version":"Preprint","arxiv":1,"abstract":[{"text":"Dynamic Connectivity is a fundamental algorithmic graph problem, motivated by a wide range of applications to social and communication networks and used as a building block in various other algorithms, such as the bi-connectivity and the dynamic minimal spanning tree problems. In brief, we wish to maintain the connected components of the graph under dynamic edge insertions and deletions. In the sequential case, the problem has been well-studied from both theoretical and practical perspectives. However, much less is known about efficient concurrent solutions to this problem. This is the gap we address in this paper. We start from one of the classic data structures used to solve this problem, the Euler Tour Tree. Our first contribution is a non-blocking single-writer implementation of it. We leverage this data structure to obtain the first truly concurrent generalization of dynamic connectivity, which preserves the time complexity of its sequential counterpart, but is also scalable in practice. To achieve this, we rely on three main techniques. The first is to ensure that connectivity queries, which usually dominate real-world workloads, are non-blocking. The second non-trivial technique expands the above idea by making all queries that do not change the connectivity structure non-blocking. The third ingredient is applying fine-grained locking for updating the connected components, which allows operations on disjoint components to occur in parallel. We evaluate the resulting algorithm on various workloads, executing on both real and synthetic graphs. The results show the efficiency of each of the proposed optimizations; the most efficient variant improves the performance of a coarse-grained based implementation on realistic scenarios up to 6x on average and up to 30x when connectivity queries dominate.","lang":"eng"}],"publication_status":"published","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2105.08098"}],"day":"01","month":"07","language":[{"iso":"eng"}],"conference":{"location":"Virtual, Online","start_date":"2021-07-06","name":"SPAA: Symposium on Parallelism in Algorithms and Architectures","end_date":"2021-07-08"},"article_processing_charge":"No","doi":"10.1145/3409964.3461810","date_updated":"2022-03-18T08:45:46Z","author":[{"full_name":"Fedorov, Alexander","last_name":"Fedorov","first_name":"Alexander"},{"first_name":"Nikita","last_name":"Koval","full_name":"Koval, Nikita"},{"id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","full_name":"Alistarh, Dan-Adrian","last_name":"Alistarh","orcid":"0000-0003-3650-940X","first_name":"Dan-Adrian"}],"date_published":"2021-07-01T00:00:00Z","quality_controlled":"1","scopus_import":"1"},{"conference":{"start_date":"2021-06-14","location":"Virtual, Online","end_date":"2021-06-18","name":"SIGMETRICS: International Conference on Measurement and Modeling of Computer Systems"},"date_published":"2021-05-01T00:00:00Z","author":[{"full_name":"Foerster, Klaus-Tycho","last_name":"Foerster","first_name":"Klaus-Tycho"},{"id":"C5402D42-15BC-11E9-A202-CA2BE6697425","full_name":"Korhonen, Janne","last_name":"Korhonen","first_name":"Janne"},{"first_name":"Ami","last_name":"Paz","full_name":"Paz, Ami"},{"full_name":"Rybicki, Joel","id":"334EFD2E-F248-11E8-B48F-1D18A9856A87","first_name":"Joel","last_name":"Rybicki","orcid":"0000-0002-6432-6646"},{"first_name":"Stefan","last_name":"Schmid","full_name":"Schmid, Stefan"}],"date_updated":"2023-09-26T10:40:55Z","doi":"10.1145/3410220.3453923","related_material":{"record":[{"id":"10855","status":"public","relation":"extended_version"}]},"article_processing_charge":"No","scopus_import":"1","quality_controlled":"1","main_file_link":[{"url":"https://arxiv.org/abs/2005.07637","open_access":"1"}],"publication_status":"published","day":"01","project":[{"grant_number":"805223","name":"Elastic Coordination for Scalable Machine Learning","_id":"268A44D6-B435-11E9-9278-68D0E5697425","call_identifier":"H2020"},{"call_identifier":"H2020","_id":"26A5D39A-B435-11E9-9278-68D0E5697425","grant_number":"840605","name":"Coordination in constrained and natural distributed systems"}],"language":[{"iso":"eng"}],"month":"05","department":[{"_id":"DaAl"}],"title":"Input-dynamic distributed algorithms for communication networks","publication":"Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems","publisher":"Association for Computing Machinery","oa_version":"Preprint","ec_funded":1,"date_created":"2022-03-18T08:48:41Z","arxiv":1,"abstract":[{"text":"Consider a distributed task where the communication network is fixed but the local inputs given to the nodes of the distributed system may change over time. In this work, we explore the following question: if some of the local inputs change, can an existing solution be updated efficiently, in a dynamic and distributed manner?\r\nTo address this question, we define the batch dynamic CONGEST model in which we are given a bandwidth-limited communication network and a dynamic edge labelling defines the problem input. The task is to maintain a solution to a graph problem on the labelled graph under batch changes. We investigate, when a batch of alpha edge label changes arrive, - how much time as a function of alpha we need to update an existing solution, and - how much information the nodes have to keep in local memory between batches in order to update the solution quickly.\r\nOur work lays the foundations for the theory of input-dynamic distributed network algorithms. We give a general picture of the complexity landscape in this model, design both universal algorithms and algorithms for concrete problems, and present a general framework for lower bounds. The diverse time complexity of our model spans from constant time, through time polynomial in alpha, and to alpha time, which we show to be enough for any task.","lang":"eng"}],"page":"71-72","type":"conference","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"10854","year":"2021","status":"public","acknowledgement":"We thank Jukka Suomela for discussions. We also thank our shepherd Mohammad Hajiesmaili and the reviewers for their time and suggestions on how to improve the paper. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 805223 ScaleML), from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska–Curie grant agreement No. 840605, from the Vienna Science and Technology Fund (WWTF) project WHATIF, ICT19-045, 2020-2024, and from the Austrian Science Fund (FWF) and netIDEE SCIENCE project P 33775-N.","oa":1,"external_id":{"arxiv":["2005.07637"]},"citation":{"short":"K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, S. Schmid, in:, Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, Association for Computing Machinery, 2021, pp. 71–72.","mla":"Foerster, Klaus-Tycho, et al. “Input-Dynamic Distributed Algorithms for Communication Networks.” <i>Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems</i>, Association for Computing Machinery, 2021, pp. 71–72, doi:<a href=\"https://doi.org/10.1145/3410220.3453923\">10.1145/3410220.3453923</a>.","ista":"Foerster K-T, Korhonen J, Paz A, Rybicki J, Schmid S. 2021. Input-dynamic distributed algorithms for communication networks. Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems. SIGMETRICS: International Conference on Measurement and Modeling of Computer Systems, 71–72.","ama":"Foerster K-T, Korhonen J, Paz A, Rybicki J, Schmid S. Input-dynamic distributed algorithms for communication networks. In: <i>Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems</i>. Association for Computing Machinery; 2021:71-72. doi:<a href=\"https://doi.org/10.1145/3410220.3453923\">10.1145/3410220.3453923</a>","apa":"Foerster, K.-T., Korhonen, J., Paz, A., Rybicki, J., &#38; Schmid, S. (2021). Input-dynamic distributed algorithms for communication networks. In <i>Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems</i> (pp. 71–72). Virtual, Online: Association for Computing Machinery. <a href=\"https://doi.org/10.1145/3410220.3453923\">https://doi.org/10.1145/3410220.3453923</a>","chicago":"Foerster, Klaus-Tycho, Janne Korhonen, Ami Paz, Joel Rybicki, and Stefan Schmid. “Input-Dynamic Distributed Algorithms for Communication Networks.” In <i>Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems</i>, 71–72. Association for Computing Machinery, 2021. <a href=\"https://doi.org/10.1145/3410220.3453923\">https://doi.org/10.1145/3410220.3453923</a>.","ieee":"K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, and S. Schmid, “Input-dynamic distributed algorithms for communication networks,” in <i>Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems</i>, Virtual, Online, 2021, pp. 71–72."},"publication_identifier":{"isbn":["9781450380720"]}},{"abstract":[{"text":"Consider a distributed task where the communication network is fixed but the local inputs given to the nodes of the distributed system may change over time. In this work, we explore the following question: if some of the local inputs change, can an existing solution be updated efficiently, in a dynamic and distributed manner? To address this question, we define the batch dynamic \\congest model in which we are given a bandwidth-limited communication network and a dynamic edge labelling defines the problem input. The task is to maintain a solution to a graph problem on the labeled graph under batch changes. We investigate, when a batch of α edge label changes arrive, \\beginitemize \\item how much time as a function of α we need to update an existing solution, and \\item how much information the nodes have to keep in local memory between batches in order to update the solution quickly. \\enditemize Our work lays the foundations for the theory of input-dynamic distributed network algorithms. We give a general picture of the complexity landscape in this model, design both universal algorithms and algorithms for concrete problems, and present a general framework for lower bounds. In particular, we derive non-trivial upper bounds for two selected, contrasting problems: maintaining a minimum spanning tree and detecting cliques.","lang":"eng"}],"arxiv":1,"date_created":"2022-03-18T09:10:27Z","ec_funded":1,"oa_version":"Preprint","publication":"Proceedings of the ACM on Measurement and Analysis of Computing Systems","title":"Input-dynamic distributed algorithms for communication networks","department":[{"_id":"DaAl"}],"publisher":"Association for Computing Machinery","citation":{"apa":"Foerster, K.-T., Korhonen, J., Paz, A., Rybicki, J., &#38; Schmid, S. (2021). Input-dynamic distributed algorithms for communication networks. <i>Proceedings of the ACM on Measurement and Analysis of Computing Systems</i>. Association for Computing Machinery. <a href=\"https://doi.org/10.1145/3447384\">https://doi.org/10.1145/3447384</a>","ieee":"K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, and S. Schmid, “Input-dynamic distributed algorithms for communication networks,” <i>Proceedings of the ACM on Measurement and Analysis of Computing Systems</i>, vol. 5, no. 1. Association for Computing Machinery, pp. 1–33, 2021.","chicago":"Foerster, Klaus-Tycho, Janne Korhonen, Ami Paz, Joel Rybicki, and Stefan Schmid. “Input-Dynamic Distributed Algorithms for Communication Networks.” <i>Proceedings of the ACM on Measurement and Analysis of Computing Systems</i>. Association for Computing Machinery, 2021. <a href=\"https://doi.org/10.1145/3447384\">https://doi.org/10.1145/3447384</a>.","ista":"Foerster K-T, Korhonen J, Paz A, Rybicki J, Schmid S. 2021. Input-dynamic distributed algorithms for communication networks. Proceedings of the ACM on Measurement and Analysis of Computing Systems. 5(1), 1–33.","short":"K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, S. Schmid, Proceedings of the ACM on Measurement and Analysis of Computing Systems 5 (2021) 1–33.","mla":"Foerster, Klaus-Tycho, et al. “Input-Dynamic Distributed Algorithms for Communication Networks.” <i>Proceedings of the ACM on Measurement and Analysis of Computing Systems</i>, vol. 5, no. 1, Association for Computing Machinery, 2021, pp. 1–33, doi:<a href=\"https://doi.org/10.1145/3447384\">10.1145/3447384</a>.","ama":"Foerster K-T, Korhonen J, Paz A, Rybicki J, Schmid S. Input-dynamic distributed algorithms for communication networks. <i>Proceedings of the ACM on Measurement and Analysis of Computing Systems</i>. 2021;5(1):1-33. doi:<a href=\"https://doi.org/10.1145/3447384\">10.1145/3447384</a>"},"publication_identifier":{"issn":["2476-1249"]},"status":"public","acknowledgement":"We thank Jukka Suomela for discussions. We also thank our shepherd Mohammad Hajiesmaili\r\nand the reviewers for their time and suggestions on how to improve the paper. This project\r\nhas received funding from the European Research Council (ERC) under the European Union’s\r\nHorizon 2020 research and innovation programme (grant agreement No 805223 ScaleML), from the European Union’s Horizon 2020 research and innovation programme under the Marie\r\nSk lodowska–Curie grant agreement No. 840605, from the Vienna Science and Technology Fund (WWTF) project WHATIF, ICT19-045, 2020-2024, and from the Austrian Science Fund (FWF) and netIDEE SCIENCE project P 33775-N.","oa":1,"issue":"1","article_type":"original","external_id":{"arxiv":["2005.07637"]},"_id":"10855","year":"2021","volume":5,"page":"1-33","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"journal_article","keyword":["Computer Networks and Communications","Hardware and Architecture","Safety","Risk","Reliability and Quality","Computer Science (miscellaneous)"],"scopus_import":"1","quality_controlled":"1","author":[{"full_name":"Foerster, Klaus-Tycho","first_name":"Klaus-Tycho","last_name":"Foerster"},{"last_name":"Korhonen","first_name":"Janne","id":"C5402D42-15BC-11E9-A202-CA2BE6697425","full_name":"Korhonen, Janne"},{"first_name":"Ami","last_name":"Paz","full_name":"Paz, Ami"},{"id":"334EFD2E-F248-11E8-B48F-1D18A9856A87","full_name":"Rybicki, Joel","orcid":"0000-0002-6432-6646","last_name":"Rybicki","first_name":"Joel"},{"full_name":"Schmid, Stefan","first_name":"Stefan","last_name":"Schmid"}],"date_published":"2021-03-01T00:00:00Z","article_processing_charge":"No","doi":"10.1145/3447384","date_updated":"2023-09-26T10:40:55Z","related_material":{"record":[{"id":"10854","status":"public","relation":"shorter_version"}]},"month":"03","language":[{"iso":"eng"}],"project":[{"grant_number":"840605","name":"Coordination in constrained and natural distributed systems","_id":"26A5D39A-B435-11E9-9278-68D0E5697425","call_identifier":"H2020"},{"name":"Elastic Coordination for Scalable Machine Learning","grant_number":"805223","_id":"268A44D6-B435-11E9-9278-68D0E5697425","call_identifier":"H2020"}],"day":"01","main_file_link":[{"url":"https://arxiv.org/abs/2005.07637","open_access":"1"}],"intvolume":"         5","publication_status":"published"},{"publisher":"De Gruyter","publication":"Analysis and Geometry in Metric Spaces","department":[{"_id":"UlWa"}],"title":"On the volume of sections of the cube","date_created":"2022-03-18T09:25:14Z","oa_version":"Published Version","arxiv":1,"abstract":[{"text":"We study the properties of the maximal volume k-dimensional sections of the n-dimensional cube [−1, 1]n. We obtain a first order necessary condition for a k-dimensional subspace to be a local maximizer of the volume of such sections, which we formulate in a geometric way. We estimate the length of the projection of a vector of the standard basis of Rn onto a k-dimensional subspace that maximizes the volume of the intersection. We \u001cnd the optimal upper bound on the volume of a planar section of the cube [−1, 1]n , n ≥ 2.","lang":"eng"}],"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","type":"journal_article","volume":9,"page":"1-18","year":"2021","has_accepted_license":"1","_id":"10856","issue":"1","external_id":{"isi":["000734286800001"],"arxiv":["2004.02674"]},"article_type":"original","status":"public","acknowledgement":"The authors acknowledge the support of the grant of the Russian Government N 075-15-\r\n2019-1926. G.I.was supported also by the SwissNational Science Foundation grant 200021-179133. The authors are very grateful to the anonymous reviewer for valuable remarks.","oa":1,"publication_identifier":{"issn":["2299-3274"]},"citation":{"mla":"Ivanov, Grigory, and Igor Tsiutsiurupa. “On the Volume of Sections of the Cube.” <i>Analysis and Geometry in Metric Spaces</i>, vol. 9, no. 1, De Gruyter, 2021, pp. 1–18, doi:<a href=\"https://doi.org/10.1515/agms-2020-0103\">10.1515/agms-2020-0103</a>.","short":"G. Ivanov, I. Tsiutsiurupa, Analysis and Geometry in Metric Spaces 9 (2021) 1–18.","ista":"Ivanov G, Tsiutsiurupa I. 2021. On the volume of sections of the cube. Analysis and Geometry in Metric Spaces. 9(1), 1–18.","ama":"Ivanov G, Tsiutsiurupa I. On the volume of sections of the cube. <i>Analysis and Geometry in Metric Spaces</i>. 2021;9(1):1-18. doi:<a href=\"https://doi.org/10.1515/agms-2020-0103\">10.1515/agms-2020-0103</a>","apa":"Ivanov, G., &#38; Tsiutsiurupa, I. (2021). On the volume of sections of the cube. <i>Analysis and Geometry in Metric Spaces</i>. De Gruyter. <a href=\"https://doi.org/10.1515/agms-2020-0103\">https://doi.org/10.1515/agms-2020-0103</a>","chicago":"Ivanov, Grigory, and Igor Tsiutsiurupa. “On the Volume of Sections of the Cube.” <i>Analysis and Geometry in Metric Spaces</i>. De Gruyter, 2021. <a href=\"https://doi.org/10.1515/agms-2020-0103\">https://doi.org/10.1515/agms-2020-0103</a>.","ieee":"G. Ivanov and I. Tsiutsiurupa, “On the volume of sections of the cube,” <i>Analysis and Geometry in Metric Spaces</i>, vol. 9, no. 1. De Gruyter, pp. 1–18, 2021."},"file_date_updated":"2022-03-18T09:31:59Z","tmp":{"image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"article_processing_charge":"No","date_updated":"2023-08-17T07:07:58Z","doi":"10.1515/agms-2020-0103","date_published":"2021-01-29T00:00:00Z","author":[{"last_name":"Ivanov","first_name":"Grigory","id":"87744F66-5C6F-11EA-AFE0-D16B3DDC885E","full_name":"Ivanov, Grigory"},{"first_name":"Igor","last_name":"Tsiutsiurupa","full_name":"Tsiutsiurupa, Igor"}],"quality_controlled":"1","keyword":["Applied Mathematics","Geometry and Topology","Analysis"],"scopus_import":"1","file":[{"relation":"main_file","creator":"dernst","access_level":"open_access","content_type":"application/pdf","date_created":"2022-03-18T09:31:59Z","success":1,"date_updated":"2022-03-18T09:31:59Z","file_id":"10857","file_size":789801,"checksum":"7e615ac8489f5eae580b6517debfdc53","file_name":"2021_AnalysisMetricSpaces_Ivanov.pdf"}],"publication_status":"published","intvolume":"         9","ddc":["510"],"day":"29","isi":1,"month":"01","language":[{"iso":"eng"}]},{"abstract":[{"text":"The cost-effective conversion of low-grade heat into electricity using thermoelectric devices requires developing alternative materials and material processing technologies able to reduce the currently high device manufacturing costs. In this direction, thermoelectric materials that do not rely on rare or toxic elements such as tellurium or lead need to be produced using high-throughput technologies not involving high temperatures and long processes. Bi2Se3 is an obvious possible Te-free alternative to Bi2Te3 for ambient temperature thermoelectric applications, but its performance is still low for practical applications, and additional efforts toward finding proper dopants are required. Here, we report a scalable method to produce Bi2Se3 nanosheets at low synthesis temperatures. We studied the influence of different dopants on the thermoelectric properties of this material. Among the elements tested, we demonstrated that Sn doping resulted in the best performance. Sn incorporation resulted in a significant improvement to the Bi2Se3 Seebeck coefficient and a reduction in the thermal conductivity in the direction of the hot-press axis, resulting in an overall 60% improvement in the thermoelectric figure of merit of Bi2Se3.","lang":"eng"}],"publisher":"MDPI","publication":"Nanomaterials","title":"Enhanced thermoelectric performance of n-type Bi2Se3 nanosheets through Sn doping","department":[{"_id":"MaIb"}],"date_created":"2022-03-18T09:45:02Z","ec_funded":1,"oa_version":"Published Version","issue":"7","article_type":"original","external_id":{"isi":["000676570000001"]},"status":"public","oa":1,"acknowledgement":"M.L., Y.Z., T.Z. and K.X. thank the China Scholarship Council for their scholarship\r\nsupport. Y.L. acknowledges funding from the European Union’s Horizon 2020 research and\r\ninnovation program under the Marie Sklodowska-Curie grant agreement No. 754411. J.L. thanks the ICREA Academia program and projects MICINN/FEDER RTI2018-093996-B-C31 and G.C. 2017 SGR 128. ICN2 acknowledges funding from the Generalitat de Catalunya 2017 SGR 327 and the Spanish MINECO ENE2017-85087-C3.","publication_identifier":{"issn":["2079-4991"]},"citation":{"ama":"Li M, Zhang Y, Zhang T, et al. Enhanced thermoelectric performance of n-type Bi2Se3 nanosheets through Sn doping. <i>Nanomaterials</i>. 2021;11(7). doi:<a href=\"https://doi.org/10.3390/nano11071827\">10.3390/nano11071827</a>","short":"M. Li, Y. Zhang, T. Zhang, Y. Zuo, K. Xiao, J. Arbiol, J. Llorca, Y. Liu, A. Cabot, Nanomaterials 11 (2021).","ista":"Li M, Zhang Y, Zhang T, Zuo Y, Xiao K, Arbiol J, Llorca J, Liu Y, Cabot A. 2021. Enhanced thermoelectric performance of n-type Bi2Se3 nanosheets through Sn doping. Nanomaterials. 11(7), 1827.","mla":"Li, Mengyao, et al. “Enhanced Thermoelectric Performance of N-Type Bi2Se3 Nanosheets through Sn Doping.” <i>Nanomaterials</i>, vol. 11, no. 7, 1827, MDPI, 2021, doi:<a href=\"https://doi.org/10.3390/nano11071827\">10.3390/nano11071827</a>.","chicago":"Li, Mengyao, Yu Zhang, Ting Zhang, Yong Zuo, Ke Xiao, Jordi Arbiol, Jordi Llorca, Yu Liu, and Andreu Cabot. “Enhanced Thermoelectric Performance of N-Type Bi2Se3 Nanosheets through Sn Doping.” <i>Nanomaterials</i>. MDPI, 2021. <a href=\"https://doi.org/10.3390/nano11071827\">https://doi.org/10.3390/nano11071827</a>.","ieee":"M. Li <i>et al.</i>, “Enhanced thermoelectric performance of n-type Bi2Se3 nanosheets through Sn doping,” <i>Nanomaterials</i>, vol. 11, no. 7. MDPI, 2021.","apa":"Li, M., Zhang, Y., Zhang, T., Zuo, Y., Xiao, K., Arbiol, J., … Cabot, A. (2021). Enhanced thermoelectric performance of n-type Bi2Se3 nanosheets through Sn doping. <i>Nanomaterials</i>. MDPI. <a href=\"https://doi.org/10.3390/nano11071827\">https://doi.org/10.3390/nano11071827</a>"},"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","type":"journal_article","volume":11,"year":"2021","has_accepted_license":"1","_id":"10858","article_processing_charge":"No","date_updated":"2023-08-17T07:08:30Z","doi":"10.3390/nano11071827","author":[{"full_name":"Li, Mengyao","first_name":"Mengyao","last_name":"Li"},{"last_name":"Zhang","first_name":"Yu","full_name":"Zhang, Yu"},{"first_name":"Ting","last_name":"Zhang","full_name":"Zhang, Ting"},{"last_name":"Zuo","first_name":"Yong","full_name":"Zuo, Yong"},{"last_name":"Xiao","first_name":"Ke","full_name":"Xiao, Ke"},{"first_name":"Jordi","last_name":"Arbiol","full_name":"Arbiol, Jordi"},{"full_name":"Llorca, Jordi","first_name":"Jordi","last_name":"Llorca"},{"first_name":"Yu","orcid":"0000-0001-7313-6740","last_name":"Liu","full_name":"Liu, Yu","id":"2A70014E-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Andreu","last_name":"Cabot","full_name":"Cabot, Andreu"}],"date_published":"2021-07-14T00:00:00Z","quality_controlled":"1","keyword":["General Materials Science","General Chemical Engineering"],"scopus_import":"1","article_number":"1827","file_date_updated":"2022-03-18T09:53:15Z","tmp":{"image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"ddc":["540"],"day":"14","isi":1,"month":"07","project":[{"_id":"260C2330-B435-11E9-9278-68D0E5697425","name":"ISTplus - Postdoctoral Fellowships","grant_number":"754411","call_identifier":"H2020"}],"language":[{"iso":"eng"}],"file":[{"content_type":"application/pdf","success":1,"date_created":"2022-03-18T09:53:15Z","relation":"main_file","creator":"dernst","access_level":"open_access","file_size":4867547,"file_name":"2021_Nanomaterials_Li.pdf","checksum":"f28a8b5cf80f5605828359bb398463b0","file_id":"10859","date_updated":"2022-03-18T09:53:15Z"}],"publication_status":"published","intvolume":"        11"},{"keyword":["General Mathematics","Tight frame","Grassmannian","zonotope"],"scopus_import":"1","quality_controlled":"1","date_published":"2021-12-18T00:00:00Z","author":[{"last_name":"Ivanov","first_name":"Grigory","id":"87744F66-5C6F-11EA-AFE0-D16B3DDC885E","full_name":"Ivanov, Grigory"}],"article_processing_charge":"No","doi":"10.4153/s000843952000096x","date_updated":"2023-09-05T12:43:09Z","main_file_link":[{"url":"https://arxiv.org/abs/1804.10055","open_access":"1"}],"intvolume":"        64","publication_status":"published","month":"12","isi":1,"language":[{"iso":"eng"}],"day":"18","date_created":"2022-03-18T09:55:59Z","oa_version":"Preprint","publication":"Canadian Mathematical Bulletin","department":[{"_id":"UlWa"}],"title":"Tight frames and related geometric problems","publisher":"Canadian Mathematical Society","abstract":[{"lang":"eng","text":"A tight frame is the orthogonal projection of some orthonormal basis of Rn onto Rk. We show that a set of vectors is a tight frame if and only if the set of all cross products of these vectors is a tight frame. We reformulate a range of problems on the volume of projections (or sections) of regular polytopes in terms of tight frames and write a first-order necessary condition for local extrema of these problems. As applications, we prove new results for the problem of maximization of the volume of zonotopes."}],"arxiv":1,"_id":"10860","year":"2021","volume":64,"page":"942-963","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","type":"journal_article","citation":{"ista":"Ivanov G. 2021. Tight frames and related geometric problems. Canadian Mathematical Bulletin. 64(4), 942–963.","short":"G. Ivanov, Canadian Mathematical Bulletin 64 (2021) 942–963.","mla":"Ivanov, Grigory. “Tight Frames and Related Geometric Problems.” <i>Canadian Mathematical Bulletin</i>, vol. 64, no. 4, Canadian Mathematical Society, 2021, pp. 942–63, doi:<a href=\"https://doi.org/10.4153/s000843952000096x\">10.4153/s000843952000096x</a>.","ama":"Ivanov G. Tight frames and related geometric problems. <i>Canadian Mathematical Bulletin</i>. 2021;64(4):942-963. doi:<a href=\"https://doi.org/10.4153/s000843952000096x\">10.4153/s000843952000096x</a>","apa":"Ivanov, G. (2021). Tight frames and related geometric problems. <i>Canadian Mathematical Bulletin</i>. Canadian Mathematical Society. <a href=\"https://doi.org/10.4153/s000843952000096x\">https://doi.org/10.4153/s000843952000096x</a>","chicago":"Ivanov, Grigory. “Tight Frames and Related Geometric Problems.” <i>Canadian Mathematical Bulletin</i>. Canadian Mathematical Society, 2021. <a href=\"https://doi.org/10.4153/s000843952000096x\">https://doi.org/10.4153/s000843952000096x</a>.","ieee":"G. Ivanov, “Tight frames and related geometric problems,” <i>Canadian Mathematical Bulletin</i>, vol. 64, no. 4. Canadian Mathematical Society, pp. 942–963, 2021."},"publication_identifier":{"issn":["0008-4395"],"eissn":["1496-4287"]},"oa":1,"acknowledgement":"The author was supported by the Swiss National Science Foundation grant 200021_179133. The author acknowledges the financial support from the Ministry of Education and Science of the Russian Federation in the framework of MegaGrant no. 075-15-2019-1926.","status":"public","issue":"4","article_type":"original","external_id":{"isi":["000730165300021"],"arxiv":["1804.10055"]}},{"oa_version":"Preprint","date_created":"2022-03-21T11:41:28Z","ec_funded":1,"publisher":"arXiv","department":[{"_id":"GaTk"}],"title":"Quantifying the coexistence of neuronal oscillations and avalanches","abstract":[{"text":"Brain dynamics display collective phenomena as diverse as neuronal oscillations and avalanches. Oscillations are rhythmic, with fluctuations occurring at a characteristic scale, whereas avalanches are scale-free cascades of neural activity. Here we show that such antithetic features can coexist in a very generic class of adaptive neural networks. In the most simple yet fully microscopic model from this class we make direct contact with human brain resting-state activity recordings via tractable inference of the model's two essential parameters. The inferred model quantitatively captures the dynamics over a broad range of scales, from single sensor fluctuations, collective behaviors of nearly-synchronous extreme events on multiple sensors, to neuronal avalanches unfolding over multiple sensors across multiple time-bins. Importantly, the inferred parameters correlate with model-independent signatures of \"closeness to criticality\", suggesting that the coexistence of scale-specific (neural oscillations) and scale-free (neuronal avalanches) dynamics in brain activity occurs close to a non-equilibrium critical point at the onset of self-sustained oscillations.","lang":"eng"}],"date_updated":"2022-03-22T07:53:18Z","doi":"10.48550/ARXIV.2108.06686","article_processing_charge":"No","arxiv":1,"author":[{"last_name":"Lombardi","orcid":"0000-0003-2623-5249","first_name":"Fabrizio","id":"A057D288-3E88-11E9-986D-0CF4E5697425","full_name":"Lombardi, Fabrizio"},{"first_name":"Selver","last_name":"Pepic","full_name":"Pepic, Selver","id":"F93245C4-C3CA-11E9-B4F0-C6F4E5697425"},{"full_name":"Shriki, Oren","last_name":"Shriki","first_name":"Oren"},{"first_name":"Gašper","orcid":"0000-0002-6699-1455","last_name":"Tkačik","full_name":"Tkačik, Gašper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87"},{"full_name":"De Martino, Daniele","last_name":"De Martino","first_name":"Daniele"}],"date_published":"2021-08-17T00:00:00Z","publication_status":"submitted","year":"2021","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2108.06686"}],"_id":"10912","type":"preprint","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","page":"37","language":[{"iso":"eng"}],"project":[{"call_identifier":"H2020","name":"ISTplus - Postdoctoral Fellowships","grant_number":"754411","_id":"260C2330-B435-11E9-9278-68D0E5697425"},{"name":"Efficient coding with biophysical realism","grant_number":"P34015","_id":"626c45b5-2b32-11ec-9570-e509828c1ba6"}],"month":"08","citation":{"mla":"Lombardi, Fabrizio, et al. <i>Quantifying the Coexistence of Neuronal Oscillations and Avalanches</i>. arXiv, doi:<a href=\"https://doi.org/10.48550/ARXIV.2108.06686\">10.48550/ARXIV.2108.06686</a>.","short":"F. Lombardi, S. Pepic, O. Shriki, G. Tkačik, D. De Martino, (n.d.).","ista":"Lombardi F, Pepic S, Shriki O, Tkačik G, De Martino D. Quantifying the coexistence of neuronal oscillations and avalanches. <a href=\"https://doi.org/10.48550/ARXIV.2108.06686\">10.48550/ARXIV.2108.06686</a>.","ama":"Lombardi F, Pepic S, Shriki O, Tkačik G, De Martino D. Quantifying the coexistence of neuronal oscillations and avalanches. doi:<a href=\"https://doi.org/10.48550/ARXIV.2108.06686\">10.48550/ARXIV.2108.06686</a>","apa":"Lombardi, F., Pepic, S., Shriki, O., Tkačik, G., &#38; De Martino, D. (n.d.). Quantifying the coexistence of neuronal oscillations and avalanches. arXiv. <a href=\"https://doi.org/10.48550/ARXIV.2108.06686\">https://doi.org/10.48550/ARXIV.2108.06686</a>","chicago":"Lombardi, Fabrizio, Selver Pepic, Oren Shriki, Gašper Tkačik, and Daniele De Martino. “Quantifying the Coexistence of Neuronal Oscillations and Avalanches.” arXiv, n.d. <a href=\"https://doi.org/10.48550/ARXIV.2108.06686\">https://doi.org/10.48550/ARXIV.2108.06686</a>.","ieee":"F. Lombardi, S. Pepic, O. Shriki, G. Tkačik, and D. De Martino, “Quantifying the coexistence of neuronal oscillations and avalanches.” arXiv."},"day":"17","external_id":{"arxiv":["2108.06686"]},"ddc":["570"],"oa":1,"status":"public","acknowledgement":"FL acknowledges support from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Grant Agreement No. 754411. GT\r\nacknowledges the support of the Austrian Science Fund (FWF) under Stand-Alone Grant\r\nNo. P34015."},{"doi":"10.1016/j.devcel.2021.10.008","date_updated":"2022-07-18T08:26:38Z","article_processing_charge":"No","date_published":"2021-11-08T00:00:00Z","author":[{"first_name":"Shefali","last_name":"Krishna","full_name":"Krishna, Shefali"},{"last_name":"Arrojo e Drigo","first_name":"Rafael","full_name":"Arrojo e Drigo, Rafael"},{"full_name":"Capitanio, Juliana S.","first_name":"Juliana S.","last_name":"Capitanio"},{"full_name":"Ramachandra, Ranjan","last_name":"Ramachandra","first_name":"Ranjan"},{"full_name":"Ellisman, Mark","last_name":"Ellisman","first_name":"Mark"},{"full_name":"HETZER, Martin W","id":"86c0d31b-b4eb-11ec-ac5a-eae7b2e135ed","first_name":"Martin W","last_name":"HETZER","orcid":"0000-0002-2111-992X"}],"quality_controlled":"1","scopus_import":"1","keyword":["Developmental Biology","Cell Biology","General Biochemistry","Genetics and Molecular Biology","Molecular Biology"],"publication_status":"published","intvolume":"        56","day":"08","pmid":1,"language":[{"iso":"eng"}],"month":"11","publisher":"Elsevier","title":"Identification of long-lived proteins in the mitochondria reveals increased stability of the electron transport chain","publication":"Developmental Cell","oa_version":"None","date_created":"2022-04-07T07:43:14Z","extern":"1","abstract":[{"lang":"eng","text":"In order to combat molecular damage, most cellular proteins undergo rapid turnover. We have previously identified large nuclear protein assemblies that can persist for years in post-mitotic tissues and are subject to age-related decline. Here, we report that mitochondria can be long lived in the mouse brain and reveal that specific mitochondrial proteins have half-lives longer than the average proteome. These mitochondrial long-lived proteins (mitoLLPs) are core components of the electron transport chain (ETC) and display increased longevity in respiratory supercomplexes. We find that COX7C, a mitoLLP that forms a stable contact site between complexes I and IV, is required for complex IV and supercomplex assembly. Remarkably, even upon depletion of COX7C transcripts, ETC function is maintained for days, effectively uncoupling mitochondrial function from ongoing transcription of its mitoLLPs. Our results suggest that modulating protein longevity within the ETC is critical for mitochondrial proteome maintenance and the robustness of mitochondrial function."}],"type":"journal_article","user_id":"72615eeb-f1f3-11ec-aa25-d4573ddc34fd","page":"P2952-2965.e9","volume":56,"year":"2021","_id":"11052","external_id":{"pmid":["34715012"]},"article_type":"original","issue":"21","status":"public","publication_identifier":{"issn":["1534-5807"]},"citation":{"ista":"Krishna S, Arrojo e Drigo R, Capitanio JS, Ramachandra R, Ellisman M, Hetzer M. 2021. Identification of long-lived proteins in the mitochondria reveals increased stability of the electron transport chain. Developmental Cell. 56(21), P2952–2965.e9.","mla":"Krishna, Shefali, et al. “Identification of Long-Lived Proteins in the Mitochondria Reveals Increased Stability of the Electron Transport Chain.” <i>Developmental Cell</i>, vol. 56, no. 21, Elsevier, 2021, p. P2952–2965.e9, doi:<a href=\"https://doi.org/10.1016/j.devcel.2021.10.008\">10.1016/j.devcel.2021.10.008</a>.","short":"S. Krishna, R. Arrojo e Drigo, J.S. Capitanio, R. Ramachandra, M. Ellisman, M. Hetzer, Developmental Cell 56 (2021) P2952–2965.e9.","ama":"Krishna S, Arrojo e Drigo R, Capitanio JS, Ramachandra R, Ellisman M, Hetzer M. Identification of long-lived proteins in the mitochondria reveals increased stability of the electron transport chain. <i>Developmental Cell</i>. 2021;56(21):P2952-2965.e9. doi:<a href=\"https://doi.org/10.1016/j.devcel.2021.10.008\">10.1016/j.devcel.2021.10.008</a>","apa":"Krishna, S., Arrojo e Drigo, R., Capitanio, J. S., Ramachandra, R., Ellisman, M., &#38; Hetzer, M. (2021). Identification of long-lived proteins in the mitochondria reveals increased stability of the electron transport chain. <i>Developmental Cell</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.devcel.2021.10.008\">https://doi.org/10.1016/j.devcel.2021.10.008</a>","chicago":"Krishna, Shefali, Rafael Arrojo e Drigo, Juliana S. Capitanio, Ranjan Ramachandra, Mark Ellisman, and Martin Hetzer. “Identification of Long-Lived Proteins in the Mitochondria Reveals Increased Stability of the Electron Transport Chain.” <i>Developmental Cell</i>. Elsevier, 2021. <a href=\"https://doi.org/10.1016/j.devcel.2021.10.008\">https://doi.org/10.1016/j.devcel.2021.10.008</a>.","ieee":"S. Krishna, R. Arrojo e Drigo, J. S. Capitanio, R. Ramachandra, M. Ellisman, and M. Hetzer, “Identification of long-lived proteins in the mitochondria reveals increased stability of the electron transport chain,” <i>Developmental Cell</i>, vol. 56, no. 21. Elsevier, p. P2952–2965.e9, 2021."}},{"status":"public","oa":1,"issue":"5","article_type":"original","external_id":{"pmid":["34370163"]},"citation":{"short":"G.S. Shadel, P.D. Adams, W.T. Berggren, J.K. Diedrich, K.E. Diffenderfer, F.H. Gage, N. Hah, M. Hansen, M. Hetzer, A.J.A. Molina, U. Manor, K. Marek, D.D. O’Keefe, A.F.M. Pinto, A. Sacco, T.O. Sharpee, M.N. Shokriev, S. Zambetti, GeroScience 43 (2021) 2139–2148.","ista":"Shadel GS, Adams PD, Berggren WT, Diedrich JK, Diffenderfer KE, Gage FH, Hah N, Hansen M, Hetzer M, Molina AJA, Manor U, Marek K, O’Keefe DD, Pinto AFM, Sacco A, Sharpee TO, Shokriev MN, Zambetti S. 2021. The San Diego Nathan Shock Center: Tackling the heterogeneity of aging. GeroScience. 43(5), 2139–2148.","mla":"Shadel, Gerald S., et al. “The San Diego Nathan Shock Center: Tackling the Heterogeneity of Aging.” <i>GeroScience</i>, vol. 43, no. 5, Springer Nature, 2021, pp. 2139–48, doi:<a href=\"https://doi.org/10.1007/s11357-021-00426-x\">10.1007/s11357-021-00426-x</a>.","ama":"Shadel GS, Adams PD, Berggren WT, et al. The San Diego Nathan Shock Center: Tackling the heterogeneity of aging. <i>GeroScience</i>. 2021;43(5):2139-2148. doi:<a href=\"https://doi.org/10.1007/s11357-021-00426-x\">10.1007/s11357-021-00426-x</a>","apa":"Shadel, G. S., Adams, P. D., Berggren, W. T., Diedrich, J. K., Diffenderfer, K. E., Gage, F. H., … Zambetti, S. (2021). The San Diego Nathan Shock Center: Tackling the heterogeneity of aging. <i>GeroScience</i>. Springer Nature. <a href=\"https://doi.org/10.1007/s11357-021-00426-x\">https://doi.org/10.1007/s11357-021-00426-x</a>","ieee":"G. S. Shadel <i>et al.</i>, “The San Diego Nathan Shock Center: Tackling the heterogeneity of aging,” <i>GeroScience</i>, vol. 43, no. 5. Springer Nature, pp. 2139–2148, 2021.","chicago":"Shadel, Gerald S., Peter D. Adams, W. Travis Berggren, Jolene K. Diedrich, Kenneth E. Diffenderfer, Fred H. Gage, Nasun Hah, et al. “The San Diego Nathan Shock Center: Tackling the Heterogeneity of Aging.” <i>GeroScience</i>. Springer Nature, 2021. <a href=\"https://doi.org/10.1007/s11357-021-00426-x\">https://doi.org/10.1007/s11357-021-00426-x</a>."},"publication_identifier":{"issn":["2509-2715","2509-2723"]},"volume":43,"page":"2139-2148","user_id":"72615eeb-f1f3-11ec-aa25-d4573ddc34fd","type":"journal_article","_id":"11053","year":"2021","abstract":[{"lang":"eng","text":"Understanding basic mechanisms of aging holds great promise for developing interventions that prevent or delay many age-related declines and diseases simultaneously to increase human healthspan. However, a major confounding factor in aging research is the heterogeneity of the aging process itself. At the organismal level, it is clear that chronological age does not always predict biological age or susceptibility to frailty or pathology. While genetics and environment are major factors driving variable rates of aging, additional complexity arises because different organs, tissues, and cell types are intrinsically heterogeneous and exhibit different aging trajectories normally or in response to the stresses of the aging process (e.g., damage accumulation). Tackling the heterogeneity of aging requires new and specialized tools (e.g., single-cell analyses, mass spectrometry-based approaches, and advanced imaging) to identify novel signatures of aging across scales. Cutting-edge computational approaches are then needed to integrate these disparate datasets and elucidate network interactions between known aging hallmarks. There is also a need for improved, human cell-based models of aging to ensure that basic research findings are relevant to human aging and healthspan interventions. The San Diego Nathan Shock Center (SD-NSC) provides access to cutting-edge scientific resources to facilitate the study of the heterogeneity of aging in general and to promote the use of novel human cell models of aging. The center also has a robust Research Development Core that funds pilot projects on the heterogeneity of aging and organizes innovative training activities, including workshops and a personalized mentoring program, to help investigators new to the aging field succeed. Finally, the SD-NSC participates in outreach activities to educate the general community about the importance of aging research and promote the need for basic biology of aging research in particular."}],"extern":"1","publication":"GeroScience","title":"The San Diego Nathan Shock Center: Tackling the heterogeneity of aging","publisher":"Springer Nature","date_created":"2022-04-07T07:43:25Z","oa_version":"Published Version","pmid":1,"day":"01","month":"10","language":[{"iso":"eng"}],"intvolume":"        43","main_file_link":[{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8599742/","open_access":"1"}],"publication_status":"published","date_published":"2021-10-01T00:00:00Z","author":[{"full_name":"Shadel, Gerald S.","last_name":"Shadel","first_name":"Gerald S."},{"first_name":"Peter D.","last_name":"Adams","full_name":"Adams, Peter D."},{"first_name":"W. Travis","last_name":"Berggren","full_name":"Berggren, W. Travis"},{"full_name":"Diedrich, Jolene K.","last_name":"Diedrich","first_name":"Jolene K."},{"last_name":"Diffenderfer","first_name":"Kenneth E.","full_name":"Diffenderfer, Kenneth E."},{"first_name":"Fred H.","last_name":"Gage","full_name":"Gage, Fred H."},{"full_name":"Hah, Nasun","first_name":"Nasun","last_name":"Hah"},{"full_name":"Hansen, Malene","last_name":"Hansen","first_name":"Malene"},{"full_name":"HETZER, Martin W","id":"86c0d31b-b4eb-11ec-ac5a-eae7b2e135ed","first_name":"Martin W","orcid":"0000-0002-2111-992X","last_name":"HETZER"},{"full_name":"Molina, Anthony J. A.","last_name":"Molina","first_name":"Anthony J. A."},{"full_name":"Manor, Uri","last_name":"Manor","first_name":"Uri"},{"full_name":"Marek, Kurt","first_name":"Kurt","last_name":"Marek"},{"first_name":"David D.","last_name":"O’Keefe","full_name":"O’Keefe, David D."},{"full_name":"Pinto, Antonio F. M.","last_name":"Pinto","first_name":"Antonio F. M."},{"full_name":"Sacco, Alessandra","last_name":"Sacco","first_name":"Alessandra"},{"full_name":"Sharpee, Tatyana O.","last_name":"Sharpee","first_name":"Tatyana O."},{"full_name":"Shokriev, Maxim N.","first_name":"Maxim N.","last_name":"Shokriev"},{"first_name":"Stefania","last_name":"Zambetti","full_name":"Zambetti, Stefania"}],"article_processing_charge":"No","doi":"10.1007/s11357-021-00426-x","date_updated":"2022-07-18T08:27:24Z","keyword":["Geriatrics and Gerontology","Aging"],"scopus_import":"1","quality_controlled":"1"},{"publication_status":"published","main_file_link":[{"open_access":"1","url":" https://doi.org/10.48550/arXiv.1905.11845"}],"intvolume":"        35","day":"18","project":[{"name":"ISTplus - Postdoctoral Fellowships","grant_number":"754411","_id":"260C2330-B435-11E9-9278-68D0E5697425","call_identifier":"H2020"},{"_id":"268A44D6-B435-11E9-9278-68D0E5697425","name":"Elastic Coordination for Scalable Machine Learning","grant_number":"805223","call_identifier":"H2020"}],"language":[{"iso":"eng"}],"month":"05","conference":{"start_date":"2021-02-02","location":"Virtual, Online","end_date":"2021-02-09","name":"AAAI: Conference on Artificial Intelligence"},"date_updated":"2022-06-07T06:53:36Z","article_processing_charge":"No","author":[{"full_name":"Kungurtsev, Vyacheslav","first_name":"Vyacheslav","last_name":"Kungurtsev"},{"full_name":"Egan, Malcolm","first_name":"Malcolm","last_name":"Egan"},{"last_name":"Chatterjee","first_name":"Bapi","id":"3C41A08A-F248-11E8-B48F-1D18A9856A87","full_name":"Chatterjee, Bapi"},{"id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","full_name":"Alistarh, Dan-Adrian","last_name":"Alistarh","orcid":"0000-0003-3650-940X","first_name":"Dan-Adrian"}],"date_published":"2021-05-18T00:00:00Z","quality_controlled":"1","scopus_import":"1","type":"conference","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","page":"8209-8216","volume":35,"year":"2021","_id":"11436","external_id":{"arxiv":["1905.11845"]},"issue":"9B","oa":1,"acknowledgement":"Vyacheslav Kungurtsev was supported by the OP VVV project CZ.02.1.01/0.0/0.0/16 019/0000765 “Research Center for Informatics. Bapi Chatterjee was supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 754411 (ISTPlus). Dan Alistarh has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 805223 ScaleML).","status":"public","publication_identifier":{"issn":["2159-5399"],"eissn":["2374-3468"],"isbn":["9781713835974"]},"citation":{"ama":"Kungurtsev V, Egan M, Chatterjee B, Alistarh D-A. Asynchronous optimization methods for efficient training of deep neural networks with guarantees. In: <i>35th AAAI Conference on Artificial Intelligence, AAAI 2021</i>. Vol 35. AAAI Press; 2021:8209-8216.","mla":"Kungurtsev, Vyacheslav, et al. “Asynchronous Optimization Methods for Efficient Training of Deep Neural Networks with Guarantees.” <i>35th AAAI Conference on Artificial Intelligence, AAAI 2021</i>, vol. 35, no. 9B, AAAI Press, 2021, pp. 8209–16.","short":"V. Kungurtsev, M. Egan, B. Chatterjee, D.-A. Alistarh, in:, 35th AAAI Conference on Artificial Intelligence, AAAI 2021, AAAI Press, 2021, pp. 8209–8216.","ista":"Kungurtsev V, Egan M, Chatterjee B, Alistarh D-A. 2021. Asynchronous optimization methods for efficient training of deep neural networks with guarantees. 35th AAAI Conference on Artificial Intelligence, AAAI 2021. AAAI: Conference on Artificial Intelligence vol. 35, 8209–8216.","ieee":"V. Kungurtsev, M. Egan, B. Chatterjee, and D.-A. Alistarh, “Asynchronous optimization methods for efficient training of deep neural networks with guarantees,” in <i>35th AAAI Conference on Artificial Intelligence, AAAI 2021</i>, Virtual, Online, 2021, vol. 35, no. 9B, pp. 8209–8216.","chicago":"Kungurtsev, Vyacheslav, Malcolm Egan, Bapi Chatterjee, and Dan-Adrian Alistarh. “Asynchronous Optimization Methods for Efficient Training of Deep Neural Networks with Guarantees.” In <i>35th AAAI Conference on Artificial Intelligence, AAAI 2021</i>, 35:8209–16. AAAI Press, 2021.","apa":"Kungurtsev, V., Egan, M., Chatterjee, B., &#38; Alistarh, D.-A. (2021). Asynchronous optimization methods for efficient training of deep neural networks with guarantees. In <i>35th AAAI Conference on Artificial Intelligence, AAAI 2021</i> (Vol. 35, pp. 8209–8216). Virtual, Online: AAAI Press."},"publisher":"AAAI Press","title":"Asynchronous optimization methods for efficient training of deep neural networks with guarantees","department":[{"_id":"DaAl"}],"publication":"35th AAAI Conference on Artificial Intelligence, AAAI 2021","oa_version":"Preprint","date_created":"2022-06-05T22:01:52Z","ec_funded":1,"arxiv":1,"abstract":[{"text":"Asynchronous distributed algorithms are a popular way to reduce synchronization costs in large-scale optimization, and in particular for neural network training. However, for nonsmooth and nonconvex objectives, few convergence guarantees exist beyond cases where closed-form proximal operator solutions are available. As training most popular deep neural networks corresponds to optimizing nonsmooth and nonconvex objectives, there is a pressing need for such convergence guarantees. In this paper, we analyze for the first time the convergence of stochastic asynchronous optimization for this general class of objectives. In particular, we focus on stochastic subgradient methods allowing for block variable partitioning, where the shared model is asynchronously updated by concurrent processes. To this end, we use a probabilistic model which captures key features of real asynchronous scheduling between concurrent processes. Under this model, we establish convergence with probability one to an invariant set for stochastic subgradient methods with momentum. From a practical perspective, one issue with the family of algorithms that we consider is that they are not efficiently supported by machine learning frameworks, which mostly focus on distributed data-parallel strategies. To address this, we propose a new implementation strategy for shared-memory based training of deep neural networks for a partitioned but shared model in single- and multi-GPU settings. Based on this implementation, we achieve on average1.2x speed-up in comparison to state-of-the-art training methods for popular image classification tasks, without compromising accuracy.","lang":"eng"}]},{"quality_controlled":"1","scopus_import":"1","keyword":["Computational Theory and Mathematics","Discrete Mathematics and Combinatorics","Geometry and Topology","Theoretical Computer Science"],"doi":"10.1007/s00454-021-00299-z","date_updated":"2023-02-23T13:26:41Z","related_material":{"record":[{"id":"8182","status":"public","relation":"earlier_version"}]},"article_processing_charge":"No","date_published":"2021-10-01T00:00:00Z","author":[{"full_name":"Avvakumov, Sergey","id":"3827DAC8-F248-11E8-B48F-1D18A9856A87","first_name":"Sergey","last_name":"Avvakumov"},{"full_name":"Kudrya, Sergey","id":"ecf01965-d252-11ea-95a5-8ada5f6c6a67","first_name":"Sergey","last_name":"Kudrya"}],"language":[{"iso":"eng"}],"month":"10","day":"01","publication_status":"published","intvolume":"        66","extern":"1","abstract":[{"text":"Suppose that n is not a prime power and not twice a prime power. We prove that for any Hausdorff compactum X with a free action of the symmetric group Sn, there exists an Sn-equivariant map X→Rn whose image avoids the diagonal {(x,x,…,x)∈Rn∣x∈R}. Previously, the special cases of this statement for certain X were usually proved using the equivartiant obstruction theory. Such calculations are difficult and may become infeasible past the first (primary) obstruction. We take a different approach which allows us to prove the vanishing of all obstructions simultaneously. The essential step in the proof is classifying the possible degrees of Sn-equivariant maps from the boundary ∂Δn−1 of (n−1)-simplex to itself. Existence of equivariant maps between spaces is important for many questions arising from discrete mathematics and geometry, such as Kneser’s conjecture, the Square Peg conjecture, the Splitting Necklace problem, and the Topological Tverberg conjecture, etc. We demonstrate the utility of our result applying it to one such question, a specific instance of envy-free division problem.","lang":"eng"}],"arxiv":1,"oa_version":"Preprint","date_created":"2022-06-17T08:45:15Z","publisher":"Springer Nature","title":"Vanishing of all equivariant obstructions and the mapping degree","publication":"Discrete & Computational Geometry","publication_identifier":{"eissn":["1432-0444"],"issn":["0179-5376"]},"citation":{"ieee":"S. Avvakumov and S. Kudrya, “Vanishing of all equivariant obstructions and the mapping degree,” <i>Discrete &#38; Computational Geometry</i>, vol. 66, no. 3. Springer Nature, pp. 1202–1216, 2021.","chicago":"Avvakumov, Sergey, and Sergey Kudrya. “Vanishing of All Equivariant Obstructions and the Mapping Degree.” <i>Discrete &#38; Computational Geometry</i>. Springer Nature, 2021. <a href=\"https://doi.org/10.1007/s00454-021-00299-z\">https://doi.org/10.1007/s00454-021-00299-z</a>.","apa":"Avvakumov, S., &#38; Kudrya, S. (2021). Vanishing of all equivariant obstructions and the mapping degree. <i>Discrete &#38; Computational Geometry</i>. Springer Nature. <a href=\"https://doi.org/10.1007/s00454-021-00299-z\">https://doi.org/10.1007/s00454-021-00299-z</a>","ama":"Avvakumov S, Kudrya S. Vanishing of all equivariant obstructions and the mapping degree. <i>Discrete &#38; Computational Geometry</i>. 2021;66(3):1202-1216. doi:<a href=\"https://doi.org/10.1007/s00454-021-00299-z\">10.1007/s00454-021-00299-z</a>","ista":"Avvakumov S, Kudrya S. 2021. Vanishing of all equivariant obstructions and the mapping degree. Discrete &#38; Computational Geometry. 66(3), 1202–1216.","short":"S. Avvakumov, S. Kudrya, Discrete &#38; Computational Geometry 66 (2021) 1202–1216.","mla":"Avvakumov, Sergey, and Sergey Kudrya. “Vanishing of All Equivariant Obstructions and the Mapping Degree.” <i>Discrete &#38; Computational Geometry</i>, vol. 66, no. 3, Springer Nature, 2021, pp. 1202–16, doi:<a href=\"https://doi.org/10.1007/s00454-021-00299-z\">10.1007/s00454-021-00299-z</a>."},"article_type":"original","external_id":{"arxiv":["1910.12628"]},"issue":"3","acknowledgement":"S. Avvakumov has received funding from the European Research Council under the European Union’s Seventh Framework Programme ERC Grant agreement ERC StG 716424–CASe. S. Kudrya was supported by the Austrian Academic Exchange Service (OeAD), ICM-2019-13577.","status":"public","year":"2021","_id":"11446","type":"journal_article","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","page":"1202-1216","volume":66},{"arxiv":1,"abstract":[{"lang":"eng","text":"We study efficient distributed algorithms for the fundamental problem of principal component analysis and leading eigenvector computation on the sphere, when the data are randomly distributed among a set of computational nodes. We propose a new quantized variant of Riemannian gradient descent to solve this problem, and prove that the algorithm converges with high probability under a set of necessary spherical-convexity properties. We give bounds on the number of bits transmitted by the algorithm under common initialization schemes, and investigate the dependency on the problem dimension in each case."}],"publisher":"Neural Information Processing Systems Foundation","department":[{"_id":"DaAl"}],"title":"Distributed principal component analysis with limited communication","publication":"Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems","oa_version":"Published Version","date_created":"2022-06-19T22:01:58Z","ec_funded":1,"external_id":{"arxiv":["2110.14391"]},"acknowledgement":"We would like to thank the anonymous reviewers for helpful comments and suggestions. We also thank Aurelien Lucchi and Antonio Orvieto for fruitful discussions at an early stage of this work. FA is partially supported by the SNSF under research project No. 192363 and conducted part of this work while at IST Austria under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 805223 ScaleML). PD partly conducted this work while at IST Austria and was supported by the European Union’s Horizon 2020 programme under the Marie Skłodowska-Curie grant agreement No. 754411.","oa":1,"status":"public","publication_identifier":{"issn":["1049-5258"],"isbn":["9781713845393"]},"citation":{"ama":"Alimisis F, Davies P, Vandereycken B, Alistarh D-A. Distributed principal component analysis with limited communication. In: <i>Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems</i>. Vol 4. Neural Information Processing Systems Foundation; 2021:2823-2834.","ista":"Alimisis F, Davies P, Vandereycken B, Alistarh D-A. 2021. Distributed principal component analysis with limited communication. Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 4, 2823–2834.","short":"F. Alimisis, P. Davies, B. Vandereycken, D.-A. Alistarh, in:, Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2021, pp. 2823–2834.","mla":"Alimisis, Foivos, et al. “Distributed Principal Component Analysis with Limited Communication.” <i>Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems</i>, vol. 4, Neural Information Processing Systems Foundation, 2021, pp. 2823–34.","chicago":"Alimisis, Foivos, Peter Davies, Bart Vandereycken, and Dan-Adrian Alistarh. “Distributed Principal Component Analysis with Limited Communication.” In <i>Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems</i>, 4:2823–34. Neural Information Processing Systems Foundation, 2021.","ieee":"F. Alimisis, P. Davies, B. Vandereycken, and D.-A. Alistarh, “Distributed principal component analysis with limited communication,” in <i>Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems</i>, Virtual, Online, 2021, vol. 4, pp. 2823–2834.","apa":"Alimisis, F., Davies, P., Vandereycken, B., &#38; Alistarh, D.-A. (2021). Distributed principal component analysis with limited communication. In <i>Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems</i> (Vol. 4, pp. 2823–2834). Virtual, Online: Neural Information Processing Systems Foundation."},"type":"conference","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","page":"2823-2834","volume":4,"year":"2021","_id":"11452","date_updated":"2022-06-20T08:31:52Z","article_processing_charge":"No","author":[{"first_name":"Foivos","last_name":"Alimisis","full_name":"Alimisis, Foivos"},{"first_name":"Peter","last_name":"Davies","orcid":"0000-0002-5646-9524","full_name":"Davies, Peter","id":"11396234-BB50-11E9-B24C-90FCE5697425"},{"last_name":"Vandereycken","first_name":"Bart","full_name":"Vandereycken, Bart"},{"first_name":"Dan-Adrian","orcid":"0000-0003-3650-940X","last_name":"Alistarh","full_name":"Alistarh, Dan-Adrian","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87"}],"date_published":"2021-12-01T00:00:00Z","quality_controlled":"1","scopus_import":"1","conference":{"name":"NeurIPS: Neural Information Processing Systems","end_date":"2021-12-14","location":"Virtual, Online","start_date":"2021-12-06"},"day":"01","project":[{"call_identifier":"H2020","name":"Elastic Coordination for Scalable Machine Learning","grant_number":"805223","_id":"268A44D6-B435-11E9-9278-68D0E5697425"},{"call_identifier":"H2020","_id":"260C2330-B435-11E9-9278-68D0E5697425","grant_number":"754411","name":"ISTplus - Postdoctoral Fellowships"}],"language":[{"iso":"eng"}],"month":"12","publication_status":"published","main_file_link":[{"url":"https://proceedings.neurips.cc/paper/2021/file/1680e9fa7b4dd5d62ece800239bb53bd-Paper.pdf","open_access":"1"}],"intvolume":"         4"},{"conference":{"name":"NeurIPS: Neural Information Processing Systems","end_date":"2021-12-14","location":"Virtual, Online","start_date":"2021-12-06"},"date_published":"2021-12-01T00:00:00Z","author":[{"full_name":"Braun, Lukas","first_name":"Lukas","last_name":"Braun"},{"first_name":"Tim P","orcid":"0000-0003-3295-6181","last_name":"Vogels","full_name":"Vogels, Tim P","id":"CB6FF8D2-008F-11EA-8E08-2637E6697425"}],"date_updated":"2022-06-20T07:12:58Z","article_processing_charge":"No","scopus_import":"1","quality_controlled":"1","intvolume":"        20","main_file_link":[{"url":"https://proceedings.neurips.cc/paper/2021/file/88e1ce84f9feef5a08d0df0334c53468-Paper.pdf","open_access":"1"}],"publication_status":"published","day":"01","language":[{"iso":"eng"}],"project":[{"_id":"c084a126-5a5b-11eb-8a69-d75314a70a87","name":"What’s in a memory? Spatiotemporal dynamics in strongly coupled recurrent neuronal networks.","grant_number":"214316/Z/18/Z"}],"month":"12","title":"Online learning of neural computations from sparse temporal feedback","department":[{"_id":"TiVo"}],"publication":"Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems","publisher":"Neural Information Processing Systems Foundation","oa_version":"Published Version","date_created":"2022-06-19T22:01:59Z","abstract":[{"lang":"eng","text":"Neuronal computations depend on synaptic connectivity and intrinsic electrophysiological properties. Synaptic connectivity determines which inputs from presynaptic neurons are integrated, while cellular properties determine how inputs are filtered over time. Unlike their biological counterparts, most computational approaches to learning in simulated neural networks are limited to changes in synaptic connectivity. However, if intrinsic parameters change, neural computations are altered drastically. Here, we include the parameters that determine the intrinsic properties,\r\ne.g., time constants and reset potential, into the learning paradigm. Using sparse feedback signals that indicate target spike times, and gradient-based parameter updates, we show that the intrinsic parameters can be learned along with the synaptic weights to produce specific input-output functions. Specifically, we use a teacher-student paradigm in which a randomly initialised leaky integrate-and-fire or resonate-and-fire neuron must recover the parameters of a teacher neuron. We show that complex temporal functions can be learned online and without backpropagation through time, relying on event-based updates only. Our results are a step towards online learning of neural computations from ungraded and unsigned sparse feedback signals with a biologically inspired learning mechanism."}],"page":"16437-16450","volume":20,"type":"conference","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"11453","year":"2021","acknowledgement":"We would like to thank Professor Dr. Henning Sprekeler for his valuable suggestions and Dr. Andrew Saxe, Milan Klöwer and Anna Wallis for their constructive feedback on the manuscript. Lukas Braun was supported by the Network of European Neuroscience Schools through their NENS Exchange Grant program, by the European Union through their European Community Action Scheme for the Mobility of University Students, the Woodward Scholarship awarded by Wadham College, Oxford and the Medical Research Council [MR/N013468/1]. Tim P. Vogels was supported by a Wellcome Trust Senior Research Fellowship [214316/Z/18/Z].","status":"public","oa":1,"citation":{"ieee":"L. Braun and T. P. Vogels, “Online learning of neural computations from sparse temporal feedback,” in <i>Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems</i>, Virtual, Online, 2021, vol. 20, pp. 16437–16450.","chicago":"Braun, Lukas, and Tim P Vogels. “Online Learning of Neural Computations from Sparse Temporal Feedback.” In <i>Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems</i>, 20:16437–50. Neural Information Processing Systems Foundation, 2021.","apa":"Braun, L., &#38; Vogels, T. P. (2021). Online learning of neural computations from sparse temporal feedback. In <i>Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems</i> (Vol. 20, pp. 16437–16450). Virtual, Online: Neural Information Processing Systems Foundation.","ama":"Braun L, Vogels TP. Online learning of neural computations from sparse temporal feedback. In: <i>Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems</i>. Vol 20. Neural Information Processing Systems Foundation; 2021:16437-16450.","mla":"Braun, Lukas, and Tim P. Vogels. “Online Learning of Neural Computations from Sparse Temporal Feedback.” <i>Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems</i>, vol. 20, Neural Information Processing Systems Foundation, 2021, pp. 16437–50.","short":"L. Braun, T.P. Vogels, in:, Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2021, pp. 16437–16450.","ista":"Braun L, Vogels TP. 2021. Online learning of neural computations from sparse temporal feedback. Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 20, 16437–16450."},"publication_identifier":{"issn":["1049-5258"],"isbn":["9781713845393"]}},{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"conference","volume":34,"page":"8557-8570","year":"2021","_id":"11458","external_id":{"arxiv":["2106.12379"]},"status":"public","oa":1,"acknowledgement":"This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 805223 ScaleML), and a CNRS PEPS grant. This research was supported by the Scientific Service Units (SSU) of IST Austria through resources provided by Scientific Computing (SciComp). We would also like to thank Christoph Lampert for his feedback on an earlier version of this work, as well as for providing hardware for the Transformer-XL experiments.","publication_identifier":{"isbn":["9781713845393"],"issn":["1049-5258"]},"citation":{"ama":"Peste E-A, Iofinova EB, Vladu A, Alistarh D-A. AC/DC: Alternating Compressed/DeCompressed training of deep neural networks. In: <i>35th Conference on Neural Information Processing Systems</i>. Vol 34. Curran Associates; 2021:8557-8570.","mla":"Peste, Elena-Alexandra, et al. “AC/DC: Alternating Compressed/DeCompressed Training of Deep Neural Networks.” <i>35th Conference on Neural Information Processing Systems</i>, vol. 34, Curran Associates, 2021, pp. 8557–70.","short":"E.-A. Peste, E.B. Iofinova, A. Vladu, D.-A. Alistarh, in:, 35th Conference on Neural Information Processing Systems, Curran Associates, 2021, pp. 8557–8570.","ista":"Peste E-A, Iofinova EB, Vladu A, Alistarh D-A. 2021. AC/DC: Alternating Compressed/DeCompressed training of deep neural networks. 35th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 34, 8557–8570.","ieee":"E.-A. Peste, E. B. Iofinova, A. Vladu, and D.-A. Alistarh, “AC/DC: Alternating Compressed/DeCompressed training of deep neural networks,” in <i>35th Conference on Neural Information Processing Systems</i>, Virtual, Online, 2021, vol. 34, pp. 8557–8570.","chicago":"Peste, Elena-Alexandra, Eugenia B Iofinova, Adrian Vladu, and Dan-Adrian Alistarh. “AC/DC: Alternating Compressed/DeCompressed Training of Deep Neural Networks.” In <i>35th Conference on Neural Information Processing Systems</i>, 34:8557–70. Curran Associates, 2021.","apa":"Peste, E.-A., Iofinova, E. B., Vladu, A., &#38; Alistarh, D.-A. (2021). AC/DC: Alternating Compressed/DeCompressed training of deep neural networks. In <i>35th Conference on Neural Information Processing Systems</i> (Vol. 34, pp. 8557–8570). Virtual, Online: Curran Associates."},"publisher":"Curran Associates","publication":"35th Conference on Neural Information Processing Systems","department":[{"_id":"GradSch"},{"_id":"DaAl"}],"title":"AC/DC: Alternating Compressed/DeCompressed training of deep neural networks","ec_funded":1,"date_created":"2022-06-20T12:11:53Z","oa_version":"Published Version","arxiv":1,"abstract":[{"lang":"eng","text":"The increasing computational requirements of deep neural networks (DNNs) have led to significant interest in obtaining DNN models that are sparse, yet accurate. Recent work has investigated the even harder case of sparse training, where the DNN weights are, for as much as possible, already sparse to reduce computational costs during training. Existing sparse training methods are often empirical and can have lower accuracy relative to the dense baseline. In this paper, we present a general approach called Alternating Compressed/DeCompressed (AC/DC) training of DNNs, demonstrate convergence for a variant of the algorithm, and show that AC/DC outperforms existing sparse training methods in accuracy at similar computational budgets; at high sparsity levels, AC/DC even outperforms existing methods that rely on accurate pre-trained dense models. An important property of AC/DC is that it allows co-training of dense and sparse models, yielding accurate sparse–dense model pairs at the end of the training process. This is useful in practice, where compressed variants may be desirable for deployment in resource-constrained settings without re-doing the entire training flow, and also provides us with insights into the accuracy gap between dense and compressed models. The code is available at: https://github.com/IST-DASLab/ACDC."}],"publication_status":"published","intvolume":"        34","main_file_link":[{"url":"https://proceedings.neurips.cc/paper/2021/file/48000647b315f6f00f913caa757a70b3-Paper.pdf","open_access":"1"}],"day":"6","month":"12","project":[{"call_identifier":"H2020","name":"Elastic Coordination for Scalable Machine Learning","grant_number":"805223","_id":"268A44D6-B435-11E9-9278-68D0E5697425"}],"language":[{"iso":"eng"}],"acknowledged_ssus":[{"_id":"ScienComp"}],"conference":{"location":"Virtual, Online","start_date":"2021-12-06","name":"NeurIPS: Neural Information Processing Systems","end_date":"2021-12-14"},"article_processing_charge":"No","related_material":{"record":[{"id":"13074","status":"public","relation":"dissertation_contains"}]},"date_updated":"2023-06-01T12:54:45Z","author":[{"id":"32D78294-F248-11E8-B48F-1D18A9856A87","full_name":"Peste, Elena-Alexandra","last_name":"Peste","first_name":"Elena-Alexandra"},{"last_name":"Iofinova","orcid":"0000-0002-7778-3221","first_name":"Eugenia B","id":"f9a17499-f6e0-11ea-865d-fdf9a3f77117","full_name":"Iofinova, Eugenia B"},{"last_name":"Vladu","first_name":"Adrian","full_name":"Vladu, Adrian"},{"full_name":"Alistarh, Dan-Adrian","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","first_name":"Dan-Adrian","last_name":"Alistarh","orcid":"0000-0003-3650-940X"}],"date_published":"2021-12-06T00:00:00Z","quality_controlled":"1","scopus_import":"1"},{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"conference","volume":34,"page":"14873-14886","year":"2021","_id":"11463","external_id":{"arxiv":["2010.08222"]},"oa":1,"acknowledgement":"We gratefully acknowledge funding the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 805223 ScaleML), as well as computational support from Amazon Web Services (AWS) EC2.","status":"public","publication_identifier":{"isbn":["9781713845393"],"issn":["1049-5258"]},"citation":{"ama":"Frantar E, Kurtic E, Alistarh D-A. M-FAC: Efficient matrix-free approximations of second-order information. In: <i>35th Conference on Neural Information Processing Systems</i>. Vol 34. Curran Associates; 2021:14873-14886.","ista":"Frantar E, Kurtic E, Alistarh D-A. 2021. M-FAC: Efficient matrix-free approximations of second-order information. 35th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 34, 14873–14886.","mla":"Frantar, Elias, et al. “M-FAC: Efficient Matrix-Free Approximations of Second-Order Information.” <i>35th Conference on Neural Information Processing Systems</i>, vol. 34, Curran Associates, 2021, pp. 14873–86.","short":"E. Frantar, E. Kurtic, D.-A. Alistarh, in:, 35th Conference on Neural Information Processing Systems, Curran Associates, 2021, pp. 14873–14886.","chicago":"Frantar, Elias, Eldar Kurtic, and Dan-Adrian Alistarh. “M-FAC: Efficient Matrix-Free Approximations of Second-Order Information.” In <i>35th Conference on Neural Information Processing Systems</i>, 34:14873–86. Curran Associates, 2021.","ieee":"E. Frantar, E. Kurtic, and D.-A. Alistarh, “M-FAC: Efficient matrix-free approximations of second-order information,” in <i>35th Conference on Neural Information Processing Systems</i>, Virtual, Online, 2021, vol. 34, pp. 14873–14886.","apa":"Frantar, E., Kurtic, E., &#38; Alistarh, D.-A. (2021). M-FAC: Efficient matrix-free approximations of second-order information. In <i>35th Conference on Neural Information Processing Systems</i> (Vol. 34, pp. 14873–14886). Virtual, Online: Curran Associates."},"publisher":"Curran Associates","publication":"35th Conference on Neural Information Processing Systems","title":"M-FAC: Efficient matrix-free approximations of second-order information","department":[{"_id":"DaAl"}],"ec_funded":1,"date_created":"2022-06-26T22:01:35Z","oa_version":"Published Version","arxiv":1,"abstract":[{"text":"Efficiently approximating local curvature information of the loss function is a key tool for optimization and compression of deep neural networks. Yet, most existing methods to approximate second-order information have high computational\r\nor storage costs, which limits their practicality. In this work, we investigate matrix-free, linear-time approaches for estimating Inverse-Hessian Vector Products (IHVPs) for the case when the Hessian can be approximated as a sum of rank-one matrices, as in the classic approximation of the Hessian by the empirical Fisher matrix. We propose two new algorithms: the first is tailored towards network compression and can compute the IHVP for dimension d, if the Hessian is given as a sum of m rank-one matrices, using O(dm2) precomputation, O(dm) cost for computing the IHVP, and query cost O(m) for any single element of the inverse Hessian. The second algorithm targets an optimization setting, where we wish to compute the product between the inverse Hessian, estimated over a sliding window of optimization steps, and a given gradient direction, as required for preconditioned SGD. We give an algorithm with cost O(dm + m2) for computing the IHVP and O(dm + m3) for adding or removing any gradient from the sliding window. These\r\ntwo algorithms yield state-of-the-art results for network pruning and optimization with lower computational overhead relative to existing second-order methods. Implementations are available at [9] and [17].","lang":"eng"}],"publication_status":"published","intvolume":"        34","main_file_link":[{"url":"https://proceedings.neurips.cc/paper/2021/file/7cfd5df443b4eb0d69886a583b33de4c-Paper.pdf","open_access":"1"}],"day":"06","month":"12","project":[{"call_identifier":"H2020","_id":"268A44D6-B435-11E9-9278-68D0E5697425","name":"Elastic Coordination for Scalable Machine Learning","grant_number":"805223"}],"language":[{"iso":"eng"}],"conference":{"name":"NeurIPS: Neural Information Processing Systems","end_date":"2021-12-14","location":"Virtual, Online","start_date":"2021-12-06"},"article_processing_charge":"No","date_updated":"2022-06-27T07:05:12Z","author":[{"last_name":"Frantar","first_name":"Elias","id":"09a8f98d-ec99-11ea-ae11-c063a7b7fe5f","full_name":"Frantar, Elias"},{"last_name":"Kurtic","first_name":"Eldar","id":"47beb3a5-07b5-11eb-9b87-b108ec578218","full_name":"Kurtic, Eldar"},{"id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","full_name":"Alistarh, Dan-Adrian","orcid":"0000-0003-3650-940X","last_name":"Alistarh","first_name":"Dan-Adrian"}],"date_published":"2021-12-06T00:00:00Z","quality_controlled":"1","scopus_import":"1"},{"citation":{"ieee":"D.-A. Alistarh and J. Korhonen, “Towards tight communication lower bounds for distributed optimisation,” in <i>35th Conference on Neural Information Processing Systems</i>, Virtual, Online, 2021, vol. 34, pp. 7254–7266.","chicago":"Alistarh, Dan-Adrian, and Janne Korhonen. “Towards Tight Communication Lower Bounds for Distributed Optimisation.” In <i>35th Conference on Neural Information Processing Systems</i>, 34:7254–66. Curran Associates, 2021.","apa":"Alistarh, D.-A., &#38; Korhonen, J. (2021). Towards tight communication lower bounds for distributed optimisation. In <i>35th Conference on Neural Information Processing Systems</i> (Vol. 34, pp. 7254–7266). Virtual, Online: Curran Associates.","ama":"Alistarh D-A, Korhonen J. Towards tight communication lower bounds for distributed optimisation. In: <i>35th Conference on Neural Information Processing Systems</i>. Vol 34. Curran Associates; 2021:7254-7266.","ista":"Alistarh D-A, Korhonen J. 2021. Towards tight communication lower bounds for distributed optimisation. 35th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 34, 7254–7266.","short":"D.-A. Alistarh, J. Korhonen, in:, 35th Conference on Neural Information Processing Systems, Curran Associates, 2021, pp. 7254–7266.","mla":"Alistarh, Dan-Adrian, and Janne Korhonen. “Towards Tight Communication Lower Bounds for Distributed Optimisation.” <i>35th Conference on Neural Information Processing Systems</i>, vol. 34, Curran Associates, 2021, pp. 7254–66."},"publication_identifier":{"issn":["1049-5258"],"isbn":["9781713845393"]},"acknowledgement":"We thank the NeurIPS reviewers for insightful comments that helped us improve the positioning of our results, as well as for pointing out the subsampling approach for complementing the randomised lower bound. We also thank Foivos Alimisis and Peter Davies for useful discussions. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 805223 ScaleML).","status":"public","oa":1,"external_id":{"arxiv":["2010.08222"]},"_id":"11464","year":"2021","page":"7254-7266","volume":34,"type":"conference","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","abstract":[{"lang":"eng","text":"We consider a standard distributed optimisation setting where N machines, each holding a d-dimensional function\r\nfi, aim to jointly minimise the sum of the functions ∑Ni=1fi(x). This problem arises naturally in large-scale distributed optimisation, where a standard solution is to apply variants of (stochastic) gradient descent. We focus on the communication complexity of this problem: our main result provides the first fully unconditional bounds on total number of bits which need to be sent and received by the N machines to solve this problem under point-to-point communication, within a given error-tolerance. Specifically, we show that Ω(Ndlogd/Nε) total bits need to be communicated between the machines to find an additive ϵ-approximation to the minimum of ∑Ni=1fi(x). The result holds for both deterministic and randomised algorithms, and, importantly, requires no assumptions on the algorithm structure. The lower bound is tight under certain restrictions on parameter values, and is matched within constant factors for quadratic objectives by a new variant of quantised gradient descent, which we describe and analyse. Our results bring over tools from communication complexity to distributed optimisation, which has potential for further applications."}],"arxiv":1,"oa_version":"Published Version","ec_funded":1,"date_created":"2022-06-26T22:01:35Z","title":"Towards tight communication lower bounds for distributed optimisation","department":[{"_id":"DaAl"}],"publication":"35th Conference on Neural Information Processing Systems","publisher":"Curran Associates","project":[{"_id":"268A44D6-B435-11E9-9278-68D0E5697425","grant_number":"805223","name":"Elastic Coordination for Scalable Machine Learning","call_identifier":"H2020"}],"language":[{"iso":"eng"}],"month":"12","day":"06","main_file_link":[{"open_access":"1","url":"https://proceedings.neurips.cc/paper/2021/file/3b92d18aa7a6176dd37d372bc2f1eb71-Paper.pdf"}],"intvolume":"        34","publication_status":"published","scopus_import":"1","quality_controlled":"1","author":[{"full_name":"Alistarh, Dan-Adrian","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","first_name":"Dan-Adrian","last_name":"Alistarh","orcid":"0000-0003-3650-940X"},{"first_name":"Janne","last_name":"Korhonen","full_name":"Korhonen, Janne","id":"C5402D42-15BC-11E9-A202-CA2BE6697425"}],"date_published":"2021-12-06T00:00:00Z","date_updated":"2022-06-27T06:54:31Z","article_processing_charge":"No","conference":{"name":"NeurIPS: Neural Information Processing Systems","end_date":"2021-12-14","location":"Virtual, Online","start_date":"2021-12-06"}},{"publication":"Astronomy & Astrophysics","title":"Recovery and analysis of rest-frame UV emission lines in 2052 galaxies observed with MUSE at 1.5 < z < 6.4","publisher":"EDP Sciences","date_created":"2022-07-06T08:49:03Z","oa_version":"Published Version","arxiv":1,"abstract":[{"lang":"eng","text":"Rest-frame ultraviolet (UV) emission lines probe electron densities, gas-phase abundances, metallicities, and ionization parameters of the emitting star-forming galaxies and their environments. The strongest main UV emission line, Lyα, has been instrumental in advancing the general knowledge of galaxy formation in the early universe. However, observing Lyα emission becomes increasingly challenging at z ≳ 6 when the neutral hydrogen fraction of the circumgalactic and intergalactic media increases. Secondary weaker UV emission lines provide important alternative methods for studying galaxy properties at high redshift. We present a large sample of rest-frame UV emission line sources at intermediate redshift for calibrating and exploring the connection between secondary UV lines and the emitting galaxies’ physical properties and their Lyα emission. The sample of 2052 emission line sources with 1.5 < z < 6.4 was collected from integral field data from the MUSE-Wide and MUSE-Deep surveys taken as part of Guaranteed Time Observations. The objects were selected through untargeted source detection (i.e., no preselection of sources as in dedicated spectroscopic campaigns) in the three-dimensional MUSE data cubes. We searched optimally extracted one-dimensional spectra of the full sample for UV emission features via emission line template matching, resulting in a sample of more than 100 rest-frame UV emission line detections. We show that the detection efficiency of (non-Lyα) UV emission lines increases with survey depth, and that the emission line strength of He IIλ1640 Å, [O III] λ1661 + O III] λ1666, and [Si III] λ1883 + Si III] λ1892 correlate with the strength of [C III] λ1907 + C III] λ1909. The rest-frame equivalent width (EW0) of [C III] λ1907 + C III] λ1909 is found to be roughly 0.22 ± 0.18 of EW0(Lyα). We measured the velocity offsets of resonant emission lines with respect to systemic tracers. For C IVλ1548 + C IVλ1551 we find that ΔvC IV ≲ 250 km s−1, whereas ΔvLyα falls in the range of 250−500 km s−1 which is in agreement with previous results from the literature. The electron density ne measured from [Si III] λ1883 + Si III] λ1892 and [C III] λ1907 + C III] λ1909 line flux ratios is generally < 105 cm−3 and the gas-phase abundance is below solar at 12 + log10(O/H)≈8. Lastly, we used “PhotoIonization Model Probability Density Functions” to infer physical parameters of the full sample and individual systems based on photoionization model parameter grids and observational constraints from our UV emission line searches. This reveals that the UV line emitters generally have ionization parameter log10(U) ≈ −2.5 and metal mass fractions that scatter around Z ≈ 10−2, that is Z ≈ 0.66 Z⊙. Value-added catalogs of the full sample of MUSE objects studied in this work and a collection of UV line emitters from the literature are provided with this paper."}],"extern":"1","volume":654,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"journal_article","_id":"11498","year":"2021","status":"public","acknowledgement":"We would like to thank Charlotte Mason for useful discussions and for providing the data for the curves shown in Fig. 13 and Dawn Erb for providing the observational data for the comparison sample studied by Steidel et al. (2014), also shown in Fig. 13. This work has been supported by the BMBF grant 05A14BAC and we acknowledge support by the Competitive Fund of the Leibniz Association through grant SAW-2015-AIP-2. AF acknowledges the support from grant PRIN MIUR2017-20173ML3WW_001. JS acknowledges the support from Vici grant 639.043.409 from the Dutch Research Council (NWO). GM received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No MARACAS – DLV-896778. This paper is based on observations collected at the European Organisation for Astronomical Research in the Southern Hemisphere under ESO programmes 094.A-0289(B), 095.A-0010(A), 096.A-0045(A), 096.A-0045(B), 094.A-0205, 095.A-0240, 096.A-0090, 097.A-0160, and 098.A-0017. This paper also makes use of observations made with the NASA/ESA Hubble Space Telescope obtained at STScI. This research made use of the following programs and open-source packages for Python and we are thankful to their developers: DS9 (Joye & Mandel 2003), Astropy (Astropy Collaboration 2013, 2018), APLpy (Robitaille & Bressert 2012), iPython (Pérez & Granger 2007), numpy (van der Walt et al. 2011), matplotlib (Hunter 2007), and SciPy (Jones et al. 2001).","oa":1,"external_id":{"arxiv":["2108.01713"]},"article_type":"original","citation":{"ieee":"K. B. Schmidt <i>et al.</i>, “Recovery and analysis of rest-frame UV emission lines in 2052 galaxies observed with MUSE at 1.5 &#60; z &#60; 6.4,” <i>Astronomy &#38; Astrophysics</i>, vol. 654. EDP Sciences, 2021.","chicago":"Schmidt, K. B., J. Kerutt, L. Wisotzki, T. Urrutia, A. Feltre, M. V. Maseda, T. Nanayakkara, et al. “Recovery and Analysis of Rest-Frame UV Emission Lines in 2052 Galaxies Observed with MUSE at 1.5 &#60; z &#60; 6.4.” <i>Astronomy &#38; Astrophysics</i>. EDP Sciences, 2021. <a href=\"https://doi.org/10.1051/0004-6361/202140876\">https://doi.org/10.1051/0004-6361/202140876</a>.","apa":"Schmidt, K. B., Kerutt, J., Wisotzki, L., Urrutia, T., Feltre, A., Maseda, M. V., … Schaye, J. (2021). Recovery and analysis of rest-frame UV emission lines in 2052 galaxies observed with MUSE at 1.5 &#60; z &#60; 6.4. <i>Astronomy &#38; Astrophysics</i>. EDP Sciences. <a href=\"https://doi.org/10.1051/0004-6361/202140876\">https://doi.org/10.1051/0004-6361/202140876</a>","ama":"Schmidt KB, Kerutt J, Wisotzki L, et al. Recovery and analysis of rest-frame UV emission lines in 2052 galaxies observed with MUSE at 1.5 &#60; z &#60; 6.4. <i>Astronomy &#38; Astrophysics</i>. 2021;654. doi:<a href=\"https://doi.org/10.1051/0004-6361/202140876\">10.1051/0004-6361/202140876</a>","mla":"Schmidt, K. B., et al. “Recovery and Analysis of Rest-Frame UV Emission Lines in 2052 Galaxies Observed with MUSE at 1.5 &#60; z &#60; 6.4.” <i>Astronomy &#38; Astrophysics</i>, vol. 654, A80, EDP Sciences, 2021, doi:<a href=\"https://doi.org/10.1051/0004-6361/202140876\">10.1051/0004-6361/202140876</a>.","ista":"Schmidt KB, Kerutt J, Wisotzki L, Urrutia T, Feltre A, Maseda MV, Nanayakkara T, Bacon R, Boogaard LA, Conseil S, Contini T, Herenz EC, Kollatschny W, Krumpe M, Leclercq F, Mahler G, Matthee JJ, Mauerhofer V, Richard J, Schaye J. 2021. Recovery and analysis of rest-frame UV emission lines in 2052 galaxies observed with MUSE at 1.5 &#60; z &#60; 6.4. Astronomy &#38; Astrophysics. 654, A80.","short":"K.B. Schmidt, J. Kerutt, L. Wisotzki, T. Urrutia, A. Feltre, M.V. Maseda, T. Nanayakkara, R. Bacon, L.A. Boogaard, S. Conseil, T. Contini, E.C. Herenz, W. Kollatschny, M. Krumpe, F. Leclercq, G. Mahler, J.J. Matthee, V. Mauerhofer, J. Richard, J. Schaye, Astronomy &#38; Astrophysics 654 (2021)."},"publication_identifier":{"eissn":["1432-0746"],"issn":["0004-6361"]},"article_number":"A80","date_published":"2021-10-15T00:00:00Z","author":[{"last_name":"Schmidt","first_name":"K. B.","full_name":"Schmidt, K. B."},{"first_name":"J.","last_name":"Kerutt","full_name":"Kerutt, J."},{"last_name":"Wisotzki","first_name":"L.","full_name":"Wisotzki, L."},{"last_name":"Urrutia","first_name":"T.","full_name":"Urrutia, T."},{"full_name":"Feltre, A.","last_name":"Feltre","first_name":"A."},{"full_name":"Maseda, M. V.","last_name":"Maseda","first_name":"M. V."},{"full_name":"Nanayakkara, T.","first_name":"T.","last_name":"Nanayakkara"},{"full_name":"Bacon, R.","first_name":"R.","last_name":"Bacon"},{"first_name":"L. A.","last_name":"Boogaard","full_name":"Boogaard, L. A."},{"last_name":"Conseil","first_name":"S.","full_name":"Conseil, S."},{"first_name":"T.","last_name":"Contini","full_name":"Contini, T."},{"full_name":"Herenz, E. C.","first_name":"E. C.","last_name":"Herenz"},{"last_name":"Kollatschny","first_name":"W.","full_name":"Kollatschny, W."},{"last_name":"Krumpe","first_name":"M.","full_name":"Krumpe, M."},{"full_name":"Leclercq, F.","last_name":"Leclercq","first_name":"F."},{"full_name":"Mahler, G.","first_name":"G.","last_name":"Mahler"},{"id":"7439a258-f3c0-11ec-9501-9df22fe06720","full_name":"Matthee, Jorryt J","last_name":"Matthee","orcid":"0000-0003-2871-127X","first_name":"Jorryt J"},{"first_name":"V.","last_name":"Mauerhofer","full_name":"Mauerhofer, V."},{"full_name":"Richard, J.","first_name":"J.","last_name":"Richard"},{"full_name":"Schaye, J.","last_name":"Schaye","first_name":"J."}],"article_processing_charge":"No","doi":"10.1051/0004-6361/202140876","date_updated":"2022-07-19T09:34:36Z","keyword":["Space and Planetary Science","Astronomy and Astrophysics","ultraviolet: galaxies / galaxies: high-redshift / galaxies: ISM / ISM: lines and bands / methods: observational / techniques: imaging spectroscopy"],"scopus_import":"1","quality_controlled":"1","intvolume":"       654","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2108.01713"}],"publication_status":"published","day":"15","month":"10","language":[{"iso":"eng"}]}]