[{"article_number":"2305128","month":"08","author":[{"full_name":"Zeng, Guifang","first_name":"Guifang","last_name":"Zeng"},{"first_name":"Qing","last_name":"Sun","full_name":"Sun, Qing"},{"full_name":"Horta, Sharona","id":"03a7e858-01b1-11ec-8b71-99ae6c4a05bc","last_name":"Horta","first_name":"Sharona"},{"full_name":"Wang, Shang","first_name":"Shang","last_name":"Wang"},{"full_name":"Lu, Xuan","last_name":"Lu","first_name":"Xuan"},{"full_name":"Zhang, Chaoyue","first_name":"Chaoyue","last_name":"Zhang"},{"full_name":"Li, Jing","last_name":"Li","first_name":"Jing"},{"full_name":"Li, Junshan","first_name":"Junshan","last_name":"Li"},{"full_name":"Ci, Lijie","last_name":"Ci","first_name":"Lijie"},{"full_name":"Tian, Yanhong","first_name":"Yanhong","last_name":"Tian"},{"id":"43C61214-F248-11E8-B48F-1D18A9856A87","first_name":"Maria","last_name":"Ibáñez","full_name":"Ibáñez, Maria","orcid":"0000-0001-5013-2843"},{"full_name":"Cabot, Andreu","first_name":"Andreu","last_name":"Cabot"}],"oa_version":"None","article_type":"original","keyword":["Mechanical Engineering","Mechanics of Materials","General Materials Science"],"citation":{"ista":"Zeng G, Sun Q, Horta S, Wang S, Lu X, Zhang C, Li J, Li J, Ci L, Tian Y, Ibáñez M, Cabot A. A layered Bi2Te3@PPy cathode for aqueous zinc ion batteries: Mechanism and application in printed flexible batteries. Advanced Materials., 2305128.","apa":"Zeng, G., Sun, Q., Horta, S., Wang, S., Lu, X., Zhang, C., … Cabot, A. (n.d.). A layered Bi2Te3@PPy cathode for aqueous zinc ion batteries: Mechanism and application in printed flexible batteries. Advanced Materials. Wiley. https://doi.org/10.1002/adma.202305128","ama":"Zeng G, Sun Q, Horta S, et al. A layered Bi2Te3@PPy cathode for aqueous zinc ion batteries: Mechanism and application in printed flexible batteries. Advanced Materials. doi:10.1002/adma.202305128","short":"G. Zeng, Q. Sun, S. Horta, S. Wang, X. Lu, C. Zhang, J. Li, J. Li, L. Ci, Y. Tian, M. Ibáñez, A. Cabot, Advanced Materials (n.d.).","mla":"Zeng, Guifang, et al. “A Layered Bi2Te3@PPy Cathode for Aqueous Zinc Ion Batteries: Mechanism and Application in Printed Flexible Batteries.” Advanced Materials, 2305128, Wiley, doi:10.1002/adma.202305128.","chicago":"Zeng, Guifang, Qing Sun, Sharona Horta, Shang Wang, Xuan Lu, Chaoyue Zhang, Jing Li, et al. “A Layered Bi2Te3@PPy Cathode for Aqueous Zinc Ion Batteries: Mechanism and Application in Printed Flexible Batteries.” Advanced Materials. Wiley, n.d. https://doi.org/10.1002/adma.202305128.","ieee":"G. Zeng et al., “A layered Bi2Te3@PPy cathode for aqueous zinc ion batteries: Mechanism and application in printed flexible batteries,” Advanced Materials. Wiley."},"date_created":"2023-10-17T10:53:56Z","abstract":[{"text":"Low‐cost, safe, and environmental‐friendly rechargeable aqueous zinc‐ion batteries (ZIBs) are promising as next‐generation energy storage devices for wearable electronics among other applications. However, sluggish ionic transport kinetics and the unstable electrode structure during ionic insertion/extraction hampers their deployment. Herein, we propose a new cathode material based on a layered metal chalcogenide (LMC), bismuth telluride (Bi2Te3), coated with polypyrrole (PPy). Taking advantage of the PPy coating, the Bi2Te3@PPy composite presents strong ionic absorption affinity, high oxidation resistance, and high structural stability. The ZIBs based on Bi2Te3@PPy cathodes exhibit high capacities and ultra‐long lifespans of over 5000 cycles. They also present outstanding stability even under bending. In addition, we analyze here the reaction mechanism using in situ X‐ray diffraction, X‐ray photoelectron spectroscopy, and computational tools and demonstrate that, in the aqueous system, Zn2+ is not inserted into the cathode as previously assumed. In contrast, proton charge storage dominates the process. Overall, this work not only shows the great potential of LMCs as ZIBs cathode materials and the advantages of PPy coating, but also clarifies the charge/discharge mechanism in rechargeable ZIBs based on LMCs.","lang":"eng"}],"status":"public","date_published":"2023-08-09T00:00:00Z","publication":"Advanced Materials","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"14435","language":[{"iso":"eng"}],"department":[{"_id":"MaIb"}],"title":"A layered Bi2Te3@PPy cathode for aqueous zinc ion batteries: Mechanism and application in printed flexible batteries","doi":"10.1002/adma.202305128","isi":1,"pmid":1,"quality_controlled":"1","external_id":{"pmid":["37555532"],"isi":["001085681000001"]},"publication_identifier":{"eissn":["1521-4095"],"issn":["0935-9648"]},"publication_status":"accepted","day":"09","publisher":"Wiley","date_updated":"2023-12-13T13:03:53Z","year":"2023","type":"journal_article","article_processing_charge":"No"},{"intvolume":" 404","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","status":"public","date_published":"2023-11-01T00:00:00Z","publication":"Communications in Mathematical Physics","abstract":[{"text":"We study the Fröhlich polaron model in R3, and establish the subleading term in the strong coupling asymptotics of its ground state energy, corresponding to the quantum corrections to the classical energy determined by the Pekar approximation.","lang":"eng"}],"date_created":"2023-10-22T22:01:13Z","scopus_import":"1","oa_version":"Published Version","volume":404,"type":"journal_article","publisher":"Springer Nature","publication_status":"published","project":[{"grant_number":"694227","name":"Analysis of quantum many-body systems","_id":"25C6DC12-B435-11E9-9278-68D0E5697425","call_identifier":"H2020"}],"quality_controlled":"1","department":[{"_id":"RoSe"}],"acknowledgement":"Funding from the European Union’s Horizon 2020 research and innovation programme under the ERC grant agreement No 694227 is acknowledged. Open access funding provided by Institute of Science and Technology (IST Austria).","language":[{"iso":"eng"}],"_id":"14441","page":"287-337","arxiv":1,"citation":{"chicago":"Brooks, Morris, and Robert Seiringer. “The Fröhlich Polaron at Strong Coupling: Part I - The Quantum Correction to the Classical Energy.” Communications in Mathematical Physics. Springer Nature, 2023. https://doi.org/10.1007/s00220-023-04841-3.","ieee":"M. Brooks and R. Seiringer, “The Fröhlich Polaron at strong coupling: Part I - The quantum correction to the classical energy,” Communications in Mathematical Physics, vol. 404. Springer Nature, pp. 287–337, 2023.","short":"M. Brooks, R. Seiringer, Communications in Mathematical Physics 404 (2023) 287–337.","mla":"Brooks, Morris, and Robert Seiringer. “The Fröhlich Polaron at Strong Coupling: Part I - The Quantum Correction to the Classical Energy.” Communications in Mathematical Physics, vol. 404, Springer Nature, 2023, pp. 287–337, doi:10.1007/s00220-023-04841-3.","ama":"Brooks M, Seiringer R. The Fröhlich Polaron at strong coupling: Part I - The quantum correction to the classical energy. Communications in Mathematical Physics. 2023;404:287-337. doi:10.1007/s00220-023-04841-3","ista":"Brooks M, Seiringer R. 2023. The Fröhlich Polaron at strong coupling: Part I - The quantum correction to the classical energy. Communications in Mathematical Physics. 404, 287–337.","apa":"Brooks, M., & Seiringer, R. (2023). The Fröhlich Polaron at strong coupling: Part I - The quantum correction to the classical energy. Communications in Mathematical Physics. Springer Nature. https://doi.org/10.1007/s00220-023-04841-3"},"ddc":["510"],"article_type":"original","file_date_updated":"2023-10-31T12:21:39Z","month":"11","author":[{"first_name":"Morris","last_name":"Brooks","id":"B7ECF9FC-AA38-11E9-AC9A-0930E6697425","orcid":"0000-0002-6249-0928","full_name":"Brooks, Morris"},{"last_name":"Seiringer","first_name":"Robert","id":"4AFD0470-F248-11E8-B48F-1D18A9856A87","full_name":"Seiringer, Robert","orcid":"0000-0002-6781-0521"}],"file":[{"success":1,"file_id":"14477","file_size":832375,"date_updated":"2023-10-31T12:21:39Z","date_created":"2023-10-31T12:21:39Z","access_level":"open_access","content_type":"application/pdf","creator":"dernst","checksum":"1ae49b39247cb6b40ff75997381581b8","file_name":"2023_CommMathPhysics_Brooks.pdf","relation":"main_file"}],"article_processing_charge":"Yes (via OA deal)","oa":1,"year":"2023","ec_funded":1,"has_accepted_license":"1","date_updated":"2023-10-31T12:22:51Z","publication_identifier":{"issn":["0010-3616"],"eissn":["1432-0916"]},"day":"01","external_id":{"arxiv":["2207.03156"]},"title":"The Fröhlich Polaron at strong coupling: Part I - The quantum correction to the classical energy","doi":"10.1007/s00220-023-04841-3"},{"oa_version":"None","scopus_import":"1","date_created":"2023-10-22T22:01:13Z","abstract":[{"lang":"eng","text":"In the presence of an obstacle, active particles condensate into a surface “wetting” layer due to persistent motion. If the obstacle is asymmetric, a rectification current arises in addition to wetting. Asymmetric geometries are therefore commonly used to concentrate microorganisms like bacteria and sperms. However, most studies neglect the fact that biological active matter is diverse, composed of individuals with distinct self-propulsions. Using simulations, we study a mixture of “fast” and “slow” active Brownian disks in two dimensions interacting with large half-disk obstacles. With this prototypical obstacle geometry, we analyze how the stationary collective behavior depends on the degree of self-propulsion “diversity,” defined as proportional to the difference between the self-propulsion speeds, while keeping the average self-propulsion speed fixed. A wetting layer rich in fast particles arises. The rectification current is amplified by speed diversity due to a superlinear dependence of rectification on self-propulsion speed, which arises from cooperative effects. Thus, the total rectification current cannot be obtained from an effective one-component active fluid with the same average self-propulsion speed, highlighting the importance of considering diversity in active matter."}],"publication":"The European Physical Journal E","date_published":"2023-10-01T00:00:00Z","status":"public","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","intvolume":" 46","department":[{"_id":"AnSa"}],"quality_controlled":"1","pmid":1,"publication_status":"published","publisher":"Springer Nature","type":"journal_article","volume":46,"author":[{"first_name":"Mauricio Nicolas","last_name":"Rojas Vega","id":"441e7207-f91f-11ec-b67c-9e6fe3d8fd6d","full_name":"Rojas Vega, Mauricio Nicolas"},{"full_name":"De Castro, Pablo","last_name":"De Castro","first_name":"Pablo"},{"full_name":"Soto, Rodrigo","last_name":"Soto","first_name":"Rodrigo"}],"article_number":"95","month":"10","article_type":"original","citation":{"ista":"Rojas Vega MN, De Castro P, Soto R. 2023. Mixtures of self-propelled particles interacting with asymmetric obstacles. The European Physical Journal E. 46(10), 95.","apa":"Rojas Vega, M. N., De Castro, P., & Soto, R. (2023). Mixtures of self-propelled particles interacting with asymmetric obstacles. The European Physical Journal E. Springer Nature. https://doi.org/10.1140/epje/s10189-023-00354-y","ama":"Rojas Vega MN, De Castro P, Soto R. Mixtures of self-propelled particles interacting with asymmetric obstacles. The European Physical Journal E. 2023;46(10). doi:10.1140/epje/s10189-023-00354-y","mla":"Rojas Vega, Mauricio Nicolas, et al. “Mixtures of Self-Propelled Particles Interacting with Asymmetric Obstacles.” The European Physical Journal E, vol. 46, no. 10, 95, Springer Nature, 2023, doi:10.1140/epje/s10189-023-00354-y.","short":"M.N. Rojas Vega, P. De Castro, R. Soto, The European Physical Journal E 46 (2023).","chicago":"Rojas Vega, Mauricio Nicolas, Pablo De Castro, and Rodrigo Soto. “Mixtures of Self-Propelled Particles Interacting with Asymmetric Obstacles.” The European Physical Journal E. Springer Nature, 2023. https://doi.org/10.1140/epje/s10189-023-00354-y.","ieee":"M. N. Rojas Vega, P. De Castro, and R. Soto, “Mixtures of self-propelled particles interacting with asymmetric obstacles,” The European Physical Journal E, vol. 46, no. 10. Springer Nature, 2023."},"issue":"10","_id":"14442","language":[{"iso":"eng"}],"acknowledgement":"MR-V and RS are supported by Fondecyt Grant No. 1220536 and Millennium Science Initiative Program NCN19_170D of ANID, Chile. P.d.C. was supported by Scholarships Nos. 2021/10139-2 and 2022/13872-5 and ICTP-SAIFR Grant No. 2021/14335-0, all granted by São Paulo Research Foundation (FAPESP), Brazil.","doi":"10.1140/epje/s10189-023-00354-y","title":"Mixtures of self-propelled particles interacting with asymmetric obstacles","external_id":{"pmid":["37819444"]},"day":"01","publication_identifier":{"issn":["1292-8941"],"eissn":["1292-895X"]},"date_updated":"2023-10-31T11:16:41Z","year":"2023","article_processing_charge":"No"},{"scopus_import":"1","date_created":"2023-10-22T22:01:14Z","oa_version":"None","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","intvolume":" 80","abstract":[{"lang":"eng","text":"Importance Climate change, pollution, urbanization, socioeconomic inequality, and psychosocial effects of the COVID-19 pandemic have caused massive changes in environmental conditions that affect brain health during the life span, both on a population level as well as on the level of the individual. How these environmental factors influence the brain, behavior, and mental illness is not well known.\r\nObservations A research strategy enabling population neuroscience to contribute to identify brain mechanisms underlying environment-related mental illness by leveraging innovative enrichment tools for data federation, geospatial observation, climate and pollution measures, digital health, and novel data integration techniques is described. This strategy can inform innovative treatments that target causal cognitive and molecular mechanisms of mental illness related to the environment. An example is presented of the environMENTAL Project that is leveraging federated cohort data of over 1.5 million European citizens and patients enriched with deep phenotyping data from large-scale behavioral neuroimaging cohorts to identify brain mechanisms related to environmental adversity underlying symptoms of depression, anxiety, stress, and substance misuse.\r\nConclusions and Relevance This research will lead to the development of objective biomarkers and evidence-based interventions that will significantly improve outcomes of environment-related mental illness."}],"publication":"JAMA Psychiatry","status":"public","date_published":"2023-10-01T00:00:00Z","publication_status":"published","publisher":"American Medical Association","department":[{"_id":"GaNo"}],"quality_controlled":"1","pmid":1,"type":"journal_article","volume":80,"article_type":"review","citation":{"ieee":"G. Schumann et al., “Addressing global environmental challenges to mental health using population neuroscience: A review,” JAMA Psychiatry, vol. 80, no. 10. American Medical Association, pp. 1066–1074, 2023.","chicago":"Schumann, Gunter, Ole A. Andreassen, Tobias Banaschewski, Vince D. Calhoun, Nicholas Clinton, Sylvane Desrivieres, Ragnhild Eek Brandlistuen, et al. “Addressing Global Environmental Challenges to Mental Health Using Population Neuroscience: A Review.” JAMA Psychiatry. American Medical Association, 2023. https://doi.org/10.1001/jamapsychiatry.2023.2996.","mla":"Schumann, Gunter, et al. “Addressing Global Environmental Challenges to Mental Health Using Population Neuroscience: A Review.” JAMA Psychiatry, vol. 80, no. 10, American Medical Association, 2023, pp. 1066–74, doi:10.1001/jamapsychiatry.2023.2996.","short":"G. Schumann, O.A. Andreassen, T. Banaschewski, V.D. Calhoun, N. Clinton, S. Desrivieres, R.E. Brandlistuen, J. Feng, S. Hese, E. Hitchen, P. Hoffmann, T. Jia, V. Jirsa, A.F. Marquand, F. Nees, M.M. Nöthen, G. Novarino, E. Polemiti, M. Ralser, M. Rapp, K. Schepanski, T. Schikowski, M. Slater, P. Sommer, B.C. Stahl, P.M. Thompson, S. Twardziok, D. Van Der Meer, H. Walter, L. Westlye, JAMA Psychiatry 80 (2023) 1066–1074.","ama":"Schumann G, Andreassen OA, Banaschewski T, et al. Addressing global environmental challenges to mental health using population neuroscience: A review. JAMA Psychiatry. 2023;80(10):1066-1074. doi:10.1001/jamapsychiatry.2023.2996","apa":"Schumann, G., Andreassen, O. A., Banaschewski, T., Calhoun, V. D., Clinton, N., Desrivieres, S., … Westlye, L. (2023). Addressing global environmental challenges to mental health using population neuroscience: A review. JAMA Psychiatry. American Medical Association. https://doi.org/10.1001/jamapsychiatry.2023.2996","ista":"Schumann G, Andreassen OA, Banaschewski T, Calhoun VD, Clinton N, Desrivieres S, Brandlistuen RE, Feng J, Hese S, Hitchen E, Hoffmann P, Jia T, Jirsa V, Marquand AF, Nees F, Nöthen MM, Novarino G, Polemiti E, Ralser M, Rapp M, Schepanski K, Schikowski T, Slater M, Sommer P, Stahl BC, Thompson PM, Twardziok S, Van Der Meer D, Walter H, Westlye L. 2023. Addressing global environmental challenges to mental health using population neuroscience: A review. JAMA Psychiatry. 80(10), 1066–1074."},"author":[{"last_name":"Schumann","first_name":"Gunter","full_name":"Schumann, Gunter"},{"last_name":"Andreassen","first_name":"Ole A.","full_name":"Andreassen, Ole A."},{"full_name":"Banaschewski, Tobias","last_name":"Banaschewski","first_name":"Tobias"},{"full_name":"Calhoun, Vince D.","first_name":"Vince D.","last_name":"Calhoun"},{"full_name":"Clinton, Nicholas","last_name":"Clinton","first_name":"Nicholas"},{"full_name":"Desrivieres, Sylvane","last_name":"Desrivieres","first_name":"Sylvane"},{"full_name":"Brandlistuen, Ragnhild Eek","first_name":"Ragnhild Eek","last_name":"Brandlistuen"},{"last_name":"Feng","first_name":"Jianfeng","full_name":"Feng, Jianfeng"},{"full_name":"Hese, Soeren","last_name":"Hese","first_name":"Soeren"},{"first_name":"Esther","last_name":"Hitchen","full_name":"Hitchen, Esther"},{"last_name":"Hoffmann","first_name":"Per","full_name":"Hoffmann, Per"},{"first_name":"Tianye","last_name":"Jia","full_name":"Jia, Tianye"},{"full_name":"Jirsa, Viktor","first_name":"Viktor","last_name":"Jirsa"},{"first_name":"Andre F.","last_name":"Marquand","full_name":"Marquand, Andre F."},{"last_name":"Nees","first_name":"Frauke","full_name":"Nees, Frauke"},{"full_name":"Nöthen, Markus M.","first_name":"Markus M.","last_name":"Nöthen"},{"first_name":"Gaia","last_name":"Novarino","id":"3E57A680-F248-11E8-B48F-1D18A9856A87","full_name":"Novarino, Gaia","orcid":"0000-0002-7673-7178"},{"first_name":"Elli","last_name":"Polemiti","full_name":"Polemiti, Elli"},{"full_name":"Ralser, Markus","last_name":"Ralser","first_name":"Markus"},{"first_name":"Michael","last_name":"Rapp","full_name":"Rapp, Michael"},{"full_name":"Schepanski, Kerstin","last_name":"Schepanski","first_name":"Kerstin"},{"full_name":"Schikowski, Tamara","first_name":"Tamara","last_name":"Schikowski"},{"last_name":"Slater","first_name":"Mel","full_name":"Slater, Mel"},{"first_name":"Peter","last_name":"Sommer","full_name":"Sommer, Peter"},{"last_name":"Stahl","first_name":"Bernd Carsten","full_name":"Stahl, Bernd Carsten"},{"full_name":"Thompson, Paul M.","last_name":"Thompson","first_name":"Paul M."},{"full_name":"Twardziok, Sven","first_name":"Sven","last_name":"Twardziok"},{"full_name":"Van Der Meer, Dennis","first_name":"Dennis","last_name":"Van Der Meer"},{"first_name":"Henrik","last_name":"Walter","full_name":"Walter, Henrik"},{"last_name":"Westlye","first_name":"Lars","full_name":"Westlye, Lars"}],"month":"10","language":[{"iso":"eng"}],"_id":"14443","page":"1066-1074","issue":"10","day":"01","publication_identifier":{"eissn":["2168-6238"]},"date_updated":"2023-10-31T12:17:20Z","doi":"10.1001/jamapsychiatry.2023.2996","title":"Addressing global environmental challenges to mental health using population neuroscience: A review","external_id":{"pmid":["37610741"]},"article_processing_charge":"No","year":"2023"},{"date_created":"2023-10-22T22:01:14Z","scopus_import":"1","oa_version":"Preprint","intvolume":" 256","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2023-09-01T00:00:00Z","status":"public","publication":"Israel Journal of Mathematics","abstract":[{"text":"We prove several results about substructures in Latin squares. First, we explain how to adapt our recent work on high-girth Steiner triple systems to the setting of Latin squares, resolving a conjecture of Linial that there exist Latin squares with arbitrarily high girth. As a consequence, we see that the number of order- n Latin squares with no intercalate (i.e., no 2×2 Latin subsquare) is at least (e−9/4n−o(n))n2. Equivalently, P[N=0]≥e−n2/4−o(n2)=e−(1+o(1))EN\r\n , where N is the number of intercalates in a uniformly random order- n Latin square. \r\nIn fact, extending recent work of Kwan, Sah, and Sawhney, we resolve the general large-deviation problem for intercalates in random Latin squares, up to constant factors in the exponent: for any constant 0<δ≤1 we have P[N≤(1−δ)EN]=exp(−Θ(n2)) and for any constant δ>0 we have P[N≥(1+δ)EN]=exp(−Θ(n4/3logn)). \r\nFinally, as an application of some new general tools for studying substructures in random Latin squares, we show that in almost all order- n Latin squares, the number of cuboctahedra (i.e., the number of pairs of possibly degenerate 2×2 submatrices with the same arrangement of symbols) is of order n4, which is the minimum possible. As observed by Gowers and Long, this number can be interpreted as measuring ``how associative'' the quasigroup associated with the Latin square is.","lang":"eng"}],"publisher":"Springer Nature","publication_status":"published","quality_controlled":"1","department":[{"_id":"MaKw"}],"volume":256,"type":"journal_article","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2202.05088","open_access":"1"}],"citation":{"ama":"Kwan MA, Sah A, Sawhney M, Simkin M. Substructures in Latin squares. Israel Journal of Mathematics. 2023;256(2):363-416. doi:10.1007/s11856-023-2513-9","ista":"Kwan MA, Sah A, Sawhney M, Simkin M. 2023. Substructures in Latin squares. Israel Journal of Mathematics. 256(2), 363–416.","apa":"Kwan, M. A., Sah, A., Sawhney, M., & Simkin, M. (2023). Substructures in Latin squares. Israel Journal of Mathematics. Springer Nature. https://doi.org/10.1007/s11856-023-2513-9","chicago":"Kwan, Matthew Alan, Ashwin Sah, Mehtaab Sawhney, and Michael Simkin. “Substructures in Latin Squares.” Israel Journal of Mathematics. Springer Nature, 2023. https://doi.org/10.1007/s11856-023-2513-9.","ieee":"M. A. Kwan, A. Sah, M. Sawhney, and M. Simkin, “Substructures in Latin squares,” Israel Journal of Mathematics, vol. 256, no. 2. Springer Nature, pp. 363–416, 2023.","mla":"Kwan, Matthew Alan, et al. “Substructures in Latin Squares.” Israel Journal of Mathematics, vol. 256, no. 2, Springer Nature, 2023, pp. 363–416, doi:10.1007/s11856-023-2513-9.","short":"M.A. Kwan, A. Sah, M. Sawhney, M. Simkin, Israel Journal of Mathematics 256 (2023) 363–416."},"arxiv":1,"article_type":"original","month":"09","author":[{"full_name":"Kwan, Matthew Alan","orcid":"0000-0002-4003-7567","id":"5fca0887-a1db-11eb-95d1-ca9d5e0453b3","first_name":"Matthew Alan","last_name":"Kwan"},{"full_name":"Sah, Ashwin","last_name":"Sah","first_name":"Ashwin"},{"last_name":"Sawhney","first_name":"Mehtaab","full_name":"Sawhney, Mehtaab"},{"full_name":"Simkin, Michael","first_name":"Michael","last_name":"Simkin"}],"acknowledgement":"Sah and Sawhney were supported by NSF Graduate Research Fellowship Program DGE-1745302. Sah was supported by the PD Soros Fellowship. Simkin was supported by the Center of Mathematical Sciences and Applications at Harvard University.","language":[{"iso":"eng"}],"_id":"14444","issue":"2","page":"363-416","date_updated":"2023-10-31T11:27:30Z","publication_identifier":{"eissn":["1565-8511"],"issn":["0021-2172"]},"day":"01","external_id":{"arxiv":["2202.05088"]},"title":"Substructures in Latin squares","doi":"10.1007/s11856-023-2513-9","article_processing_charge":"Yes (in subscription journal)","oa":1,"year":"2023"},{"volume":256,"type":"journal_article","department":[{"_id":"UlWa"}],"quality_controlled":"1","publication_status":"published","publisher":"Springer Nature","abstract":[{"lang":"eng","text":"We prove the following quantitative Borsuk–Ulam-type result (an equivariant analogue of Gromov’s Topological Overlap Theorem): Let X be a free ℤ/2-complex of dimension d with coboundary expansion at least ηk in dimension 0 ≤ k < d. Then for every equivariant map F: X →ℤ/2 ℝd, the fraction of d-simplices σ of X with 0 ∈ F (σ) is at least 2−d Π d−1k=0ηk.\r\n\r\nAs an application, we show that for every sufficiently thick d-dimensional spherical building Y and every map f: Y → ℝ2d, we have f(σ) ∩ f(τ) ≠ ∅ for a constant fraction μd > 0 of pairs {σ, τ} of d-simplices of Y. In particular, such complexes are non-embeddable into ℝ2d, which proves a conjecture of Tancer and Vorwerk for sufficiently thick spherical buildings.\r\n\r\nWe complement these results by upper bounds on the coboundary expansion of two families of simplicial complexes; this indicates some limitations to the bounds one can obtain by straighforward applications of the quantitative Borsuk–Ulam theorem. Specifically, we prove\r\n\r\n• an upper bound of (d + 1)/2d on the normalized (d − 1)-th coboundary expansion constant of complete (d + 1)-partite d-dimensional complexes (under a mild divisibility assumption on the sizes of the parts); and\r\n\r\n• an upper bound of (d + 1)/2d + ε on the normalized (d − 1)-th coboundary expansion of the d-dimensional spherical building associated with GLd+2(Fq) for any ε > 0 and sufficiently large q. This disproves, in a rather strong sense, a conjecture of Lubotzky, Meshulam and Mozes."}],"date_published":"2023-09-01T00:00:00Z","status":"public","publication":"Israel Journal of Mathematics","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"intvolume":" 256","oa_version":"Published Version","scopus_import":"1","date_created":"2023-10-22T22:01:14Z","has_accepted_license":"1","year":"2023","article_processing_charge":"Yes (via OA deal)","oa":1,"title":"Coboundary expansion, equivariant overlap, and crossing numbers of simplicial complexes","doi":"10.1007/s11856-023-2521-9","isi":1,"external_id":{"isi":["001081646400010"]},"publication_identifier":{"issn":["0021-2172"],"eissn":["1565-8511"]},"day":"01","date_updated":"2023-12-13T13:09:07Z","page":"675-717","issue":"2","_id":"14445","language":[{"iso":"eng"}],"file_date_updated":"2023-10-31T11:20:31Z","month":"09","author":[{"orcid":"0000-0002-1494-0568","full_name":"Wagner, Uli","first_name":"Uli","last_name":"Wagner","id":"36690CA2-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Wild, Pascal","id":"4C20D868-F248-11E8-B48F-1D18A9856A87","first_name":"Pascal","last_name":"Wild"}],"file":[{"file_size":623787,"success":1,"file_id":"14475","access_level":"open_access","date_updated":"2023-10-31T11:20:31Z","date_created":"2023-10-31T11:20:31Z","content_type":"application/pdf","file_name":"2023_IsraelJourMath_Wagner.pdf","relation":"main_file","creator":"dernst","checksum":"fbb05619fe4b650f341cc730425dd9c3"}],"article_type":"original","citation":{"mla":"Wagner, Uli, and Pascal Wild. “Coboundary Expansion, Equivariant Overlap, and Crossing Numbers of Simplicial Complexes.” Israel Journal of Mathematics, vol. 256, no. 2, Springer Nature, 2023, pp. 675–717, doi:10.1007/s11856-023-2521-9.","short":"U. Wagner, P. Wild, Israel Journal of Mathematics 256 (2023) 675–717.","ieee":"U. Wagner and P. Wild, “Coboundary expansion, equivariant overlap, and crossing numbers of simplicial complexes,” Israel Journal of Mathematics, vol. 256, no. 2. Springer Nature, pp. 675–717, 2023.","chicago":"Wagner, Uli, and Pascal Wild. “Coboundary Expansion, Equivariant Overlap, and Crossing Numbers of Simplicial Complexes.” Israel Journal of Mathematics. Springer Nature, 2023. https://doi.org/10.1007/s11856-023-2521-9.","apa":"Wagner, U., & Wild, P. (2023). Coboundary expansion, equivariant overlap, and crossing numbers of simplicial complexes. Israel Journal of Mathematics. Springer Nature. https://doi.org/10.1007/s11856-023-2521-9","ista":"Wagner U, Wild P. 2023. Coboundary expansion, equivariant overlap, and crossing numbers of simplicial complexes. Israel Journal of Mathematics. 256(2), 675–717.","ama":"Wagner U, Wild P. Coboundary expansion, equivariant overlap, and crossing numbers of simplicial complexes. Israel Journal of Mathematics. 2023;256(2):675-717. doi:10.1007/s11856-023-2521-9"},"ddc":["510"]},{"scopus_import":"1","date_created":"2023-10-22T22:01:15Z","oa_version":"Published Version","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","tmp":{"image":"/images/cc_by_nc_nd.png","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","short":"CC BY-NC-ND (4.0)","name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)"},"license":"https://creativecommons.org/licenses/by-nc-nd/4.0/","intvolume":" 23","abstract":[{"text":"Recent work has paid close attention to the first principle of Granger causality, according to which cause precedes effect. In this context, the question may arise whether the detected direction of causality also reverses after the time reversal of unidirectionally coupled data. Recently, it has been shown that for unidirectionally causally connected autoregressive (AR) processes X → Y, after time reversal of data, the opposite causal direction Y → X is indeed detected, although typically as part of the bidirectional X↔ Y link. As we argue here, the answer is different when the measured data are not from AR processes but from linked deterministic systems. When the goal is the usual forward data analysis, cross-mapping-like approaches correctly detect X → Y, while Granger causality-like approaches, which should not be used for deterministic time series, detect causal independence X → Y. The results of backward causal analysis depend on the predictability of the reversed data. Unlike AR processes, observables from deterministic dynamical systems, even complex nonlinear ones, can be predicted well forward, while backward predictions can be difficult (notably when the time reversal of a function leads to one-to-many relations). To address this problem, we propose an approach based on models that provide multiple candidate predictions for the target, combined with a loss function that consideres only the best candidate. The resulting good forward and backward predictability supports the view that unidirectionally causally linked deterministic dynamical systems X → Y can be expected to detect the same link both before and after time reversal.","lang":"eng"}],"date_published":"2023-08-01T00:00:00Z","status":"public","publication":"Measurement Science Review","publication_status":"published","publisher":"Sciendo","department":[{"_id":"ChLa"}],"quality_controlled":"1","volume":23,"type":"journal_article","article_type":"original","citation":{"ama":"Jakubík J, Phuong M, Chvosteková M, Krakovská A. Against the flow of time with multi-output models. Measurement Science Review. 2023;23(4):175-183. doi:10.2478/msr-2023-0023","ista":"Jakubík J, Phuong M, Chvosteková M, Krakovská A. 2023. Against the flow of time with multi-output models. Measurement Science Review. 23(4), 175–183.","apa":"Jakubík, J., Phuong, M., Chvosteková, M., & Krakovská, A. (2023). Against the flow of time with multi-output models. Measurement Science Review. Sciendo. https://doi.org/10.2478/msr-2023-0023","chicago":"Jakubík, Jozef, Mary Phuong, Martina Chvosteková, and Anna Krakovská. “Against the Flow of Time with Multi-Output Models.” Measurement Science Review. Sciendo, 2023. https://doi.org/10.2478/msr-2023-0023.","ieee":"J. Jakubík, M. Phuong, M. Chvosteková, and A. Krakovská, “Against the flow of time with multi-output models,” Measurement Science Review, vol. 23, no. 4. Sciendo, pp. 175–183, 2023.","mla":"Jakubík, Jozef, et al. “Against the Flow of Time with Multi-Output Models.” Measurement Science Review, vol. 23, no. 4, Sciendo, 2023, pp. 175–83, doi:10.2478/msr-2023-0023.","short":"J. Jakubík, M. Phuong, M. Chvosteková, A. Krakovská, Measurement Science Review 23 (2023) 175–183."},"ddc":["510"],"month":"08","file_date_updated":"2023-10-31T12:07:23Z","author":[{"full_name":"Jakubík, Jozef","first_name":"Jozef","last_name":"Jakubík"},{"last_name":"Bui Thi Mai","first_name":"Phuong","id":"3EC6EE64-F248-11E8-B48F-1D18A9856A87","full_name":"Bui Thi Mai, Phuong"},{"full_name":"Chvosteková, Martina","first_name":"Martina","last_name":"Chvosteková"},{"full_name":"Krakovská, Anna","first_name":"Anna","last_name":"Krakovská"}],"file":[{"date_created":"2023-10-31T12:07:23Z","date_updated":"2023-10-31T12:07:23Z","access_level":"open_access","file_id":"14476","success":1,"file_size":2639783,"creator":"dernst","checksum":"b069cc10fa6a7c96b2bc9f728165f9e6","file_name":"2023_MeasurementScienceRev_Jakubik.pdf","relation":"main_file","content_type":"application/pdf"}],"acknowledgement":"The work was supported by the Scientific Grant Agency of the Ministry of Education of the Slovak Republic and the Slovak Academy of Sciences, projects APVV-21-0216, VEGA2-0096-21 and VEGA 2-0023-22.","_id":"14446","language":[{"iso":"eng"}],"page":"175-183","issue":"4","publication_identifier":{"eissn":["1335-8871"]},"day":"01","date_updated":"2023-10-31T12:12:47Z","title":"Against the flow of time with multi-output models","doi":"10.2478/msr-2023-0023","article_processing_charge":"Yes","oa":1,"has_accepted_license":"1","year":"2023"},{"publication":"Plant Growth Regulation","date_published":"2023-10-13T00:00:00Z","status":"public","abstract":[{"text":"Auxin belongs among major phytohormones and governs multiple aspects of plant growth and development. The establishment of auxin concentration gradients, determines, among other processes, plant organ positioning and growth responses to environmental stimuli.\r\nHerein we report the synthesis of new NBD- or DNS-labelled IAA derivatives and the elucidation of their biological activity, fluorescence properties and subcellular accumulation patterns in planta. These novel compounds did not show auxin-like activity, but instead antagonized physiological auxin effects. The DNS-labelled derivatives FL5 and FL6 showed strong anti-auxin activity in roots and hypocotyls, which also occurred at the level of gene transcription as confirmed by quantitative PCR analysis. The auxin antagonism of our derivatives was further demonstrated in vitro using an SPR-based binding assay. The NBD-labelled compound FL4 with the best fluorescence properties proved to be unsuitable to study auxin accumulation patterns in planta. On the other hand, the strongest anti-auxin activity possessing compounds FL5 and FL6 could be useful to study binding mechanisms to auxin receptors and for manipulations of auxin-regulated processes.","lang":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa_version":"Published Version","date_created":"2023-10-22T22:01:15Z","scopus_import":"1","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1007/s10725-023-01083-0"}],"type":"journal_article","quality_controlled":"1","department":[{"_id":"JiFr"}],"publisher":"Springer Nature","publication_status":"epub_ahead","language":[{"iso":"eng"}],"_id":"14447","acknowledgement":"The authors would like to thank Karolína Kubiasová and Iñigo Saiz-Fernández for valuable scientific discussions. Open access publishing supported by the National Technical Library in Prague. This work was supported by the Palacký University Olomouc Young Researcher Grant Competition (JG_2020_002), by the Internal Grant Agency of Palacký University Olomouc (IGA_PrF_2023_016, IGA_PrF_2023_031), by the Ministry of Education, Youth and Sports of the Czech Republic through the European Regional Development Fund-Project Plants as a tool for sustainable global development (CZ.02.1.01/0.0/0.0/16_019/0000827) and the project Support of mobility at Palacký University Olomouc II. (CZ.02.2.69/0.0/0.0/18_053/0016919). The Biacore T200 SPR instrument was provided by the WISB Research Technology Facility within the School of Life Sciences, University of Warwick.","author":[{"full_name":"Bieleszová, Kristýna","last_name":"Bieleszová","first_name":"Kristýna"},{"first_name":"Pavel","last_name":"Hladík","full_name":"Hladík, Pavel"},{"first_name":"Martin","last_name":"Kubala","full_name":"Kubala, Martin"},{"full_name":"Napier, Richard","first_name":"Richard","last_name":"Napier"},{"first_name":"Federica","last_name":"Brunoni","full_name":"Brunoni, Federica"},{"orcid":"0000-0003-4783-1752","full_name":"Gelová, Zuzana","first_name":"Zuzana","last_name":"Gelová","id":"0AE74790-0E0B-11E9-ABC7-1ACFE5697425"},{"full_name":"Fiedler, Lukas","id":"7c417475-8972-11ed-ae7b-8b674ca26986","last_name":"Fiedler","first_name":"Lukas"},{"first_name":"Ivan","last_name":"Kulich","id":"57a1567c-8314-11eb-9063-c9ddc3451a54","full_name":"Kulich, Ivan"},{"full_name":"Strnad, Miroslav","last_name":"Strnad","first_name":"Miroslav"},{"first_name":"Karel","last_name":"Doležal","full_name":"Doležal, Karel"},{"full_name":"Novák, Ondřej","last_name":"Novák","first_name":"Ondřej"},{"full_name":"Friml, Jiří","orcid":"0000-0002-8302-7596","id":"4159519E-F248-11E8-B48F-1D18A9856A87","first_name":"Jiří","last_name":"Friml"},{"last_name":"Žukauskaitė","first_name":"Asta","full_name":"Žukauskaitė, Asta"}],"month":"10","citation":{"ista":"Bieleszová K, Hladík P, Kubala M, Napier R, Brunoni F, Gelová Z, Fiedler L, Kulich I, Strnad M, Doležal K, Novák O, Friml J, Žukauskaitė A. 2023. New fluorescent auxin derivatives: anti-auxin activity and accumulation patterns in Arabidopsis thaliana. Plant Growth Regulation.","apa":"Bieleszová, K., Hladík, P., Kubala, M., Napier, R., Brunoni, F., Gelová, Z., … Žukauskaitė, A. (2023). New fluorescent auxin derivatives: anti-auxin activity and accumulation patterns in Arabidopsis thaliana. Plant Growth Regulation. Springer Nature. https://doi.org/10.1007/s10725-023-01083-0","ama":"Bieleszová K, Hladík P, Kubala M, et al. New fluorescent auxin derivatives: anti-auxin activity and accumulation patterns in Arabidopsis thaliana. Plant Growth Regulation. 2023. doi:10.1007/s10725-023-01083-0","mla":"Bieleszová, Kristýna, et al. “New Fluorescent Auxin Derivatives: Anti-Auxin Activity and Accumulation Patterns in Arabidopsis Thaliana.” Plant Growth Regulation, Springer Nature, 2023, doi:10.1007/s10725-023-01083-0.","short":"K. Bieleszová, P. Hladík, M. Kubala, R. Napier, F. Brunoni, Z. Gelová, L. Fiedler, I. Kulich, M. Strnad, K. Doležal, O. Novák, J. Friml, A. Žukauskaitė, Plant Growth Regulation (2023).","chicago":"Bieleszová, Kristýna, Pavel Hladík, Martin Kubala, Richard Napier, Federica Brunoni, Zuzana Gelová, Lukas Fiedler, et al. “New Fluorescent Auxin Derivatives: Anti-Auxin Activity and Accumulation Patterns in Arabidopsis Thaliana.” Plant Growth Regulation. Springer Nature, 2023. https://doi.org/10.1007/s10725-023-01083-0.","ieee":"K. Bieleszová et al., “New fluorescent auxin derivatives: anti-auxin activity and accumulation patterns in Arabidopsis thaliana,” Plant Growth Regulation. Springer Nature, 2023."},"article_type":"original","year":"2023","oa":1,"article_processing_charge":"Yes (via OA deal)","external_id":{"isi":["001084334300001"]},"isi":1,"doi":"10.1007/s10725-023-01083-0","title":"New fluorescent auxin derivatives: anti-auxin activity and accumulation patterns in Arabidopsis thaliana","date_updated":"2023-12-13T13:08:25Z","day":"13","publication_identifier":{"eissn":["1573-5087"],"issn":["0167-6903"]}},{"page":"11980-11989","_id":"14448","language":[{"iso":"eng"}],"month":"08","author":[{"full_name":"Kolmogorov, Vladimir","last_name":"Kolmogorov","first_name":"Vladimir","id":"3D50B0BA-F248-11E8-B48F-1D18A9856A87"}],"citation":{"apa":"Kolmogorov, V. (2023). Solving relaxations of MAP-MRF problems: Combinatorial in-face Frank-Wolfe directions. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Vol. 2023, pp. 11980–11989). Vancouver, Canada: IEEE. https://doi.org/10.1109/CVPR52729.2023.01153","ista":"Kolmogorov V. 2023. Solving relaxations of MAP-MRF problems: Combinatorial in-face Frank-Wolfe directions. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR: Conference on Computer Vision and Pattern Recognition vol. 2023, 11980–11989.","ama":"Kolmogorov V. Solving relaxations of MAP-MRF problems: Combinatorial in-face Frank-Wolfe directions. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Vol 2023. IEEE; 2023:11980-11989. doi:10.1109/CVPR52729.2023.01153","short":"V. Kolmogorov, in:, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE, 2023, pp. 11980–11989.","mla":"Kolmogorov, Vladimir. “Solving Relaxations of MAP-MRF Problems: Combinatorial in-Face Frank-Wolfe Directions.” Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2023, IEEE, 2023, pp. 11980–89, doi:10.1109/CVPR52729.2023.01153.","ieee":"V. Kolmogorov, “Solving relaxations of MAP-MRF problems: Combinatorial in-face Frank-Wolfe directions,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vancouver, Canada, 2023, vol. 2023, pp. 11980–11989.","chicago":"Kolmogorov, Vladimir. “Solving Relaxations of MAP-MRF Problems: Combinatorial in-Face Frank-Wolfe Directions.” In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2023:11980–89. IEEE, 2023. https://doi.org/10.1109/CVPR52729.2023.01153."},"arxiv":1,"year":"2023","conference":{"location":"Vancouver, Canada","name":"CVPR: Conference on Computer Vision and Pattern Recognition","start_date":"2023-06-17","end_date":"2023-06-24"},"article_processing_charge":"No","oa":1,"external_id":{"arxiv":["2010.09567"]},"title":"Solving relaxations of MAP-MRF problems: Combinatorial in-face Frank-Wolfe directions","doi":"10.1109/CVPR52729.2023.01153","date_updated":"2023-10-31T12:01:24Z","publication_identifier":{"isbn":["9798350301298"],"issn":["1063-6919"]},"day":"22","date_published":"2023-08-22T00:00:00Z","status":"public","publication":"Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition","abstract":[{"lang":"eng","text":"We consider the problem of solving LP relaxations of MAP-MRF inference problems, and in particular the method proposed recently in [16], [35]. As a key computational subroutine, it uses a variant of the Frank-Wolfe (FW) method to minimize a smooth convex function over a combinatorial polytope. We propose an efficient implementation of this subroutine based on in-face Frank-Wolfe directions, introduced in [4] in a different context. More generally, we define an abstract data structure for a combinatorial subproblem that enables in-face FW directions, and describe its specialization for tree-structured MAP-MRF inference subproblems. Experimental results indicate that the resulting method is the current state-of-art LP solver for some classes of problems. Our code is available at pub.ist.ac.at/~vnk/papers/IN-FACE-FW.html."}],"intvolume":" 2023","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa_version":"Preprint","date_created":"2023-10-22T22:01:16Z","scopus_import":"1","main_file_link":[{"open_access":"1","url":" https://doi.org/10.48550/arXiv.2010.09567"}],"volume":2023,"type":"conference","quality_controlled":"1","department":[{"_id":"VlKo"}],"publisher":"IEEE","publication_status":"published"},{"year":"2023","has_accepted_license":"1","oa":1,"article_processing_charge":"Yes","isi":1,"external_id":{"isi":["001080536000001"],"pmid":["37808321"]},"title":"Advancing microbiome research with machine learning: Key findings from the ML4Microbiome COST action","doi":"10.3389/fmicb.2023.1257002","date_updated":"2023-12-13T13:07:21Z","publication_identifier":{"eissn":["1664-302X"]},"day":"25","acknowledgement":"This study is based upon work from COST Action ML4Microbiome “Statistical and machine learning techniques in human microbiome studies” (CA18131), supported by COST (European Cooperation in Science and Technology), www.cost.eu. MB acknowledges support through the Metagenopolis grant ANR-11-DPBS-0001. IM-I acknowledges support by the “Miguel Servet Type II” program (CPII21/00013) of the ISCIII-Madrid (Spain), co-financed by the FEDER.\r\nThe authors are grateful to all COST Action CA18131 “Statistical and machine learning techniques in human microbiome studies” members for their contribution to the COST Action objectives, and to COST (European Cooperation in Science and Technology) for the economic support, www.cost.eu. WG2 and WG3 thank Emmanuelle Le Chatelier and Pauline Barbet (Université Paris-Saclay, INRAE, MetaGenoPolis, 78350, Jouy-en-Josas, France) for preparing the shotgun CRC benchmark dataset.","language":[{"iso":"eng"}],"_id":"14449","month":"09","file_date_updated":"2023-10-30T13:38:48Z","article_number":"1257002","author":[{"full_name":"D’Elia, Domenica","last_name":"D’Elia","first_name":"Domenica"},{"full_name":"Truu, Jaak","first_name":"Jaak","last_name":"Truu"},{"full_name":"Lahti, Leo","last_name":"Lahti","first_name":"Leo"},{"first_name":"Magali","last_name":"Berland","full_name":"Berland, Magali"},{"first_name":"Georgios","last_name":"Papoutsoglou","full_name":"Papoutsoglou, Georgios"},{"last_name":"Ceci","first_name":"Michelangelo","full_name":"Ceci, Michelangelo"},{"full_name":"Zomer, Aldert","first_name":"Aldert","last_name":"Zomer"},{"full_name":"Lopes, Marta B.","last_name":"Lopes","first_name":"Marta B."},{"last_name":"Ibrahimi","first_name":"Eliana","full_name":"Ibrahimi, Eliana"},{"first_name":"Aleksandra","last_name":"Gruca","full_name":"Gruca, Aleksandra"},{"full_name":"Nechyporenko, Alina","last_name":"Nechyporenko","first_name":"Alina"},{"full_name":"Frohme, Marcus","last_name":"Frohme","first_name":"Marcus"},{"first_name":"Thomas","last_name":"Klammsteiner","full_name":"Klammsteiner, Thomas"},{"last_name":"Pau","first_name":"Enrique Carrillo De Santa","full_name":"Pau, Enrique Carrillo De Santa"},{"first_name":"Laura Judith","last_name":"Marcos-Zambrano","full_name":"Marcos-Zambrano, Laura Judith"},{"last_name":"Hron","first_name":"Karel","full_name":"Hron, Karel"},{"first_name":"Gianvito","last_name":"Pio","full_name":"Pio, Gianvito"},{"last_name":"Simeon","first_name":"Andrea","full_name":"Simeon, Andrea"},{"first_name":"Ramona","last_name":"Suharoschi","full_name":"Suharoschi, Ramona"},{"first_name":"Isabel","last_name":"Moreno-Indias","full_name":"Moreno-Indias, Isabel"},{"last_name":"Temko","first_name":"Andriy","full_name":"Temko, Andriy"},{"full_name":"Nedyalkova, Miroslava","last_name":"Nedyalkova","first_name":"Miroslava"},{"full_name":"Apostol, Elena Simona","last_name":"Apostol","first_name":"Elena Simona"},{"full_name":"Truică, Ciprian Octavian","first_name":"Ciprian Octavian","last_name":"Truică"},{"full_name":"Shigdel, Rajesh","first_name":"Rajesh","last_name":"Shigdel"},{"full_name":"Telalović, Jasminka Hasić","first_name":"Jasminka Hasić","last_name":"Telalović"},{"first_name":"Erik","last_name":"Bongcam-Rudloff","full_name":"Bongcam-Rudloff, Erik"},{"full_name":"Przymus, Piotr","last_name":"Przymus","first_name":"Piotr"},{"last_name":"Jordamović","first_name":"Naida Babić","full_name":"Jordamović, Naida Babić"},{"first_name":"Laurent","last_name":"Falquet","full_name":"Falquet, Laurent"},{"first_name":"Sonia","last_name":"Tarazona","full_name":"Tarazona, Sonia"},{"last_name":"Sampri","first_name":"Alexia","full_name":"Sampri, Alexia"},{"last_name":"Isola","first_name":"Gaetano","full_name":"Isola, Gaetano"},{"full_name":"Pérez-Serrano, David","first_name":"David","last_name":"Pérez-Serrano"},{"full_name":"Trajkovik, Vladimir","last_name":"Trajkovik","first_name":"Vladimir"},{"first_name":"Lubos","last_name":"Klucar","full_name":"Klucar, Lubos"},{"first_name":"Tatjana","last_name":"Loncar-Turukalo","full_name":"Loncar-Turukalo, Tatjana"},{"full_name":"Havulinna, Aki S.","last_name":"Havulinna","first_name":"Aki S."},{"id":"837b2259-bcc9-11ed-a196-ae55927bc6e2","first_name":"Christian","last_name":"Jansen","full_name":"Jansen, Christian"},{"last_name":"Bertelsen","first_name":"Randi J.","full_name":"Bertelsen, Randi J."},{"last_name":"Claesson","first_name":"Marcus Joakim","full_name":"Claesson, Marcus Joakim"}],"file":[{"content_type":"application/pdf","file_name":"2023_FrontiersMicrobiology_DElia.pdf","relation":"main_file","checksum":"6c0acdd8fa111a699826957b8dff19d5","creator":"dernst","file_size":505078,"file_id":"14471","success":1,"access_level":"open_access","date_created":"2023-10-30T13:38:48Z","date_updated":"2023-10-30T13:38:48Z"}],"citation":{"chicago":"D’Elia, Domenica, Jaak Truu, Leo Lahti, Magali Berland, Georgios Papoutsoglou, Michelangelo Ceci, Aldert Zomer, et al. “Advancing Microbiome Research with Machine Learning: Key Findings from the ML4Microbiome COST Action.” Frontiers in Microbiology. Frontiers, 2023. https://doi.org/10.3389/fmicb.2023.1257002.","ieee":"D. D’Elia et al., “Advancing microbiome research with machine learning: Key findings from the ML4Microbiome COST action,” Frontiers in Microbiology, vol. 14. Frontiers, 2023.","short":"D. D’Elia, J. Truu, L. Lahti, M. Berland, G. Papoutsoglou, M. Ceci, A. Zomer, M.B. Lopes, E. Ibrahimi, A. Gruca, A. Nechyporenko, M. Frohme, T. Klammsteiner, E.C.D.S. Pau, L.J. Marcos-Zambrano, K. Hron, G. Pio, A. Simeon, R. Suharoschi, I. Moreno-Indias, A. Temko, M. Nedyalkova, E.S. Apostol, C.O. Truică, R. Shigdel, J.H. Telalović, E. Bongcam-Rudloff, P. Przymus, N.B. Jordamović, L. Falquet, S. Tarazona, A. Sampri, G. Isola, D. Pérez-Serrano, V. Trajkovik, L. Klucar, T. Loncar-Turukalo, A.S. Havulinna, C. Jansen, R.J. Bertelsen, M.J. Claesson, Frontiers in Microbiology 14 (2023).","mla":"D’Elia, Domenica, et al. “Advancing Microbiome Research with Machine Learning: Key Findings from the ML4Microbiome COST Action.” Frontiers in Microbiology, vol. 14, 1257002, Frontiers, 2023, doi:10.3389/fmicb.2023.1257002.","ama":"D’Elia D, Truu J, Lahti L, et al. Advancing microbiome research with machine learning: Key findings from the ML4Microbiome COST action. Frontiers in Microbiology. 2023;14. doi:10.3389/fmicb.2023.1257002","ista":"D’Elia D, Truu J, Lahti L, Berland M, Papoutsoglou G, Ceci M, Zomer A, Lopes MB, Ibrahimi E, Gruca A, Nechyporenko A, Frohme M, Klammsteiner T, Pau ECDS, Marcos-Zambrano LJ, Hron K, Pio G, Simeon A, Suharoschi R, Moreno-Indias I, Temko A, Nedyalkova M, Apostol ES, Truică CO, Shigdel R, Telalović JH, Bongcam-Rudloff E, Przymus P, Jordamović NB, Falquet L, Tarazona S, Sampri A, Isola G, Pérez-Serrano D, Trajkovik V, Klucar L, Loncar-Turukalo T, Havulinna AS, Jansen C, Bertelsen RJ, Claesson MJ. 2023. Advancing microbiome research with machine learning: Key findings from the ML4Microbiome COST action. Frontiers in Microbiology. 14, 1257002.","apa":"D’Elia, D., Truu, J., Lahti, L., Berland, M., Papoutsoglou, G., Ceci, M., … Claesson, M. J. (2023). Advancing microbiome research with machine learning: Key findings from the ML4Microbiome COST action. Frontiers in Microbiology. Frontiers. https://doi.org/10.3389/fmicb.2023.1257002"},"ddc":["000"],"article_type":"original","volume":14,"type":"journal_article","pmid":1,"quality_controlled":"1","department":[{"_id":"ScienComp"}],"publisher":"Frontiers","publication_status":"published","date_published":"2023-09-25T00:00:00Z","status":"public","publication":"Frontiers in Microbiology","abstract":[{"text":"The rapid development of machine learning (ML) techniques has opened up the data-dense field of microbiome research for novel therapeutic, diagnostic, and prognostic applications targeting a wide range of disorders, which could substantially improve healthcare practices in the era of precision medicine. However, several challenges must be addressed to exploit the benefits of ML in this field fully. In particular, there is a need to establish “gold standard” protocols for conducting ML analysis experiments and improve interactions between microbiome researchers and ML experts. The Machine Learning Techniques in Human Microbiome Studies (ML4Microbiome) COST Action CA18131 is a European network established in 2019 to promote collaboration between discovery-oriented microbiome researchers and data-driven ML experts to optimize and standardize ML approaches for microbiome analysis. This perspective paper presents the key achievements of ML4Microbiome, which include identifying predictive and discriminatory ‘omics’ features, improving repeatability and comparability, developing automation procedures, and defining priority areas for the novel development of ML methods targeting the microbiome. The insights gained from ML4Microbiome will help to maximize the potential of ML in microbiome research and pave the way for new and improved healthcare practices.","lang":"eng"}],"intvolume":" 14","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa_version":"Published Version","date_created":"2023-10-22T22:01:16Z","scopus_import":"1"},{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","abstract":[{"text":"We investigate the potential of Multi-Objective, Deep Reinforcement Learning for stock and cryptocurrency single-asset trading: in particular, we consider a Multi-Objective algorithm which generalizes the reward functions and discount factor (i.e., these components are not specified a priori, but incorporated in the learning process). Firstly, using several important assets (BTCUSD, ETHUSDT, XRPUSDT, AAPL, SPY, NIFTY50), we verify the reward generalization property of the proposed Multi-Objective algorithm, and provide preliminary statistical evidence showing increased predictive stability over the corresponding Single-Objective strategy. Secondly, we show that the Multi-Objective algorithm has a clear edge over the corresponding Single-Objective strategy when the reward mechanism is sparse (i.e., when non-null feedback is infrequent over time). Finally, we discuss the generalization properties with respect to the discount factor. The entirety of our code is provided in open-source format.","lang":"eng"}],"date_published":"2023-10-05T00:00:00Z","status":"public","publication":"Neural Computing and Applications","scopus_import":"1","date_created":"2023-10-22T22:01:16Z","oa_version":"Published Version","type":"journal_article","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1007/s00521-023-09033-7"}],"publication_status":"epub_ahead","publisher":"Springer Nature","department":[{"_id":"JuFi"}],"project":[{"grant_number":"F6504","name":"Taming Complexity in Partial Differential Systems","_id":"fc31cba2-9c52-11eb-aca3-ff467d239cd2"},{"name":"ISTplus - Postdoctoral Fellowships","_id":"260C2330-B435-11E9-9278-68D0E5697425","grant_number":"754411","call_identifier":"H2020"}],"quality_controlled":"1","acknowledgement":"Open access funding provided by Università degli Studi di Trieste within the CRUI-CARE Agreement. Funding was provided by Austrian Science Fund (Grant No. F65), Horizon 2020 (Grant No. 754411) and Österreichische Forschungsförderungsgesellschaft.","_id":"14451","language":[{"iso":"eng"}],"article_type":"original","citation":{"ama":"Cornalba F, Disselkamp C, Scassola D, Helf C. Multi-objective reward generalization: improving performance of Deep Reinforcement Learning for applications in single-asset trading. Neural Computing and Applications. 2023. doi:10.1007/s00521-023-09033-7","apa":"Cornalba, F., Disselkamp, C., Scassola, D., & Helf, C. (2023). Multi-objective reward generalization: improving performance of Deep Reinforcement Learning for applications in single-asset trading. Neural Computing and Applications. Springer Nature. https://doi.org/10.1007/s00521-023-09033-7","ista":"Cornalba F, Disselkamp C, Scassola D, Helf C. 2023. Multi-objective reward generalization: improving performance of Deep Reinforcement Learning for applications in single-asset trading. Neural Computing and Applications.","ieee":"F. Cornalba, C. Disselkamp, D. Scassola, and C. Helf, “Multi-objective reward generalization: improving performance of Deep Reinforcement Learning for applications in single-asset trading,” Neural Computing and Applications. Springer Nature, 2023.","chicago":"Cornalba, Federico, Constantin Disselkamp, Davide Scassola, and Christopher Helf. “Multi-Objective Reward Generalization: Improving Performance of Deep Reinforcement Learning for Applications in Single-Asset Trading.” Neural Computing and Applications. Springer Nature, 2023. https://doi.org/10.1007/s00521-023-09033-7.","mla":"Cornalba, Federico, et al. “Multi-Objective Reward Generalization: Improving Performance of Deep Reinforcement Learning for Applications in Single-Asset Trading.” Neural Computing and Applications, Springer Nature, 2023, doi:10.1007/s00521-023-09033-7.","short":"F. Cornalba, C. Disselkamp, D. Scassola, C. Helf, Neural Computing and Applications (2023)."},"arxiv":1,"month":"10","author":[{"full_name":"Cornalba, Federico","orcid":"0000-0002-6269-5149","first_name":"Federico","last_name":"Cornalba","id":"2CEB641C-A400-11E9-A717-D712E6697425"},{"first_name":"Constantin","last_name":"Disselkamp","full_name":"Disselkamp, Constantin"},{"full_name":"Scassola, Davide","last_name":"Scassola","first_name":"Davide"},{"last_name":"Helf","first_name":"Christopher","full_name":"Helf, Christopher"}],"oa":1,"article_processing_charge":"Yes (via OA deal)","ec_funded":1,"year":"2023","publication_identifier":{"eissn":["1433-3058"],"issn":["0941-0643"]},"day":"05","date_updated":"2023-10-31T10:58:28Z","title":"Multi-objective reward generalization: improving performance of Deep Reinforcement Learning for applications in single-asset trading","doi":"10.1007/s00521-023-09033-7","external_id":{"arxiv":["2203.04579"]}},{"language":[{"iso":"eng"}],"_id":"14452","acknowledgement":"NHB was supported in part by ERC Grants 250152 and 101055327. AV was partly supported by the chaire Modélisation Mathématique et Biodiversité of Veolia Environment—Ecole Polytechnique—Museum National d’Histoire Naturelle—Fondation X.","issue":"2","article_type":"original","ddc":["570"],"citation":{"ieee":"N. H. Barton, A. M. Etheridge, and A. Véber, “The infinitesimal model with dominance,” Genetics, vol. 225, no. 2. Oxford Academic, 2023.","chicago":"Barton, Nicholas H, Alison M. Etheridge, and Amandine Véber. “The Infinitesimal Model with Dominance.” Genetics. Oxford Academic, 2023. https://doi.org/10.1093/genetics/iyad133.","mla":"Barton, Nicholas H., et al. “The Infinitesimal Model with Dominance.” Genetics, vol. 225, no. 2, iyad133, Oxford Academic, 2023, doi:10.1093/genetics/iyad133.","short":"N.H. Barton, A.M. Etheridge, A. Véber, Genetics 225 (2023).","ama":"Barton NH, Etheridge AM, Véber A. The infinitesimal model with dominance. Genetics. 2023;225(2). doi:10.1093/genetics/iyad133","apa":"Barton, N. H., Etheridge, A. M., & Véber, A. (2023). The infinitesimal model with dominance. Genetics. Oxford Academic. https://doi.org/10.1093/genetics/iyad133","ista":"Barton NH, Etheridge AM, Véber A. 2023. The infinitesimal model with dominance. Genetics. 225(2), iyad133."},"arxiv":1,"author":[{"first_name":"Nicholas H","last_name":"Barton","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8548-5240","full_name":"Barton, Nicholas H"},{"full_name":"Etheridge, Alison M.","first_name":"Alison M.","last_name":"Etheridge"},{"full_name":"Véber, Amandine","first_name":"Amandine","last_name":"Véber"}],"file":[{"content_type":"application/pdf","creator":"dernst","checksum":"3f65b1fbe813e2f4dbb5d2b5e891844a","file_name":"2023_Genetics_Barton.pdf","relation":"main_file","file_id":"14469","success":1,"file_size":1439032,"date_created":"2023-10-30T12:57:53Z","date_updated":"2023-10-30T12:57:53Z","access_level":"open_access"}],"month":"10","article_number":"iyad133","file_date_updated":"2023-10-30T12:57:53Z","article_processing_charge":"Yes (in subscription journal)","oa":1,"has_accepted_license":"1","related_material":{"record":[{"status":"public","id":"12949","relation":"research_data"}]},"year":"2023","ec_funded":1,"day":"01","publication_identifier":{"issn":["0016-6731"],"eissn":["1943-2631"]},"date_updated":"2025-05-28T11:42:48Z","doi":"10.1093/genetics/iyad133","title":"The infinitesimal model with dominance","external_id":{"arxiv":["2211.03515"]},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"intvolume":" 225","abstract":[{"lang":"eng","text":"The classical infinitesimal model is a simple and robust model for the inheritance of quantitative traits. In this model, a quantitative trait is expressed as the sum of a genetic and an environmental component, and the genetic component of offspring traits within a family follows a normal distribution around the average of the parents’ trait values, and has a variance that is independent of the parental traits. In previous work, we showed that when trait values are determined by the sum of a large number of additive Mendelian factors, each of small effect, one can justify the infinitesimal model as a limit of Mendelian inheritance. In this paper, we show that this result extends to include dominance. We define the model in terms of classical quantities of quantitative genetics, before justifying it as a limit of Mendelian inheritance as the number, M, of underlying loci tends to infinity. As in the additive case, the multivariate normal distribution of trait values across the pedigree can be expressed in terms of variance components in an ancestral population and probabilities of identity by descent determined by the pedigree. Now, with just first-order dominance effects, we require two-, three-, and four-way identities. We also show that, even if we condition on parental trait values, the “shared” and “residual” components of trait values within each family will be asymptotically normally distributed as the number of loci tends to infinity, with an error of order 1/M−−√. We illustrate our results with some numerical examples."}],"publication":"Genetics","date_published":"2023-10-01T00:00:00Z","status":"public","scopus_import":"1","date_created":"2023-10-29T23:01:15Z","oa_version":"Published Version","type":"journal_article","volume":225,"publication_status":"published","publisher":"Oxford Academic","department":[{"_id":"NiBa"}],"quality_controlled":"1","project":[{"call_identifier":"FP7","grant_number":"250152","name":"Limits to selection in biology and in evolutionary computation","_id":"25B07788-B435-11E9-9278-68D0E5697425"},{"grant_number":"101055327","_id":"bd6958e0-d553-11ed-ba76-86eba6a76c00","name":"Understanding the evolution of continuous genomes"}]},{"issue":"10","language":[{"iso":"eng"}],"_id":"14453","acknowledgement":"The authors gratefully acknowledge funding from the European Research Council under the European Union's Horizon 2020 research and innovation program (Project CLUSTER, Grant Agreement No. 805041). This work is also supported by a PhD fellowship funded by the Ecole Normale Supérieure de Paris-Saclay. Authors are also grateful to Benjamin Filider, who was of great help and support in the development of ideas. Eventually, we would like to thank Martin Singh, John M. Peters and an anonymous reviewer for their valuable comments and suggestions, which greatly improved the quality of the manuscript.","author":[{"first_name":"Sophie","last_name":"Abramian","full_name":"Abramian, Sophie"},{"orcid":"0000-0001-5836-5350","full_name":"Muller, Caroline J","id":"f978ccb0-3f7f-11eb-b193-b0e2bd13182b","last_name":"Muller","first_name":"Caroline J"},{"first_name":"Camille","last_name":"Risi","full_name":"Risi, Camille"}],"file":[{"success":1,"file_id":"14470","file_size":1975210,"date_updated":"2023-10-30T13:31:42Z","date_created":"2023-10-30T13:31:42Z","access_level":"open_access","content_type":"application/pdf","checksum":"43e6a1a35b663843c7d3f8d0caaca1a5","creator":"dernst","relation":"main_file","file_name":"2023_JAMES_Abramian.pdf"}],"article_number":"e2022MS003477","file_date_updated":"2023-10-30T13:31:42Z","month":"10","ddc":["550"],"citation":{"short":"S. Abramian, C.J. Muller, C. Risi, Journal of Advances in Modeling Earth Systems 15 (2023).","mla":"Abramian, Sophie, et al. “Extreme Precipitation in Tropical Squall Lines.” Journal of Advances in Modeling Earth Systems, vol. 15, no. 10, e2022MS003477, Wiley, 2023, doi:10.1029/2022MS003477.","chicago":"Abramian, Sophie, Caroline J Muller, and Camille Risi. “Extreme Precipitation in Tropical Squall Lines.” Journal of Advances in Modeling Earth Systems. Wiley, 2023. https://doi.org/10.1029/2022MS003477.","ieee":"S. Abramian, C. J. Muller, and C. Risi, “Extreme precipitation in tropical squall lines,” Journal of Advances in Modeling Earth Systems, vol. 15, no. 10. Wiley, 2023.","ista":"Abramian S, Muller CJ, Risi C. 2023. Extreme precipitation in tropical squall lines. Journal of Advances in Modeling Earth Systems. 15(10), e2022MS003477.","apa":"Abramian, S., Muller, C. J., & Risi, C. (2023). Extreme precipitation in tropical squall lines. Journal of Advances in Modeling Earth Systems. Wiley. https://doi.org/10.1029/2022MS003477","ama":"Abramian S, Muller CJ, Risi C. Extreme precipitation in tropical squall lines. Journal of Advances in Modeling Earth Systems. 2023;15(10). doi:10.1029/2022MS003477"},"article_type":"original","ec_funded":1,"year":"2023","has_accepted_license":"1","oa":1,"article_processing_charge":"Yes","external_id":{"isi":["001084933600001"]},"isi":1,"doi":"10.1029/2022MS003477","title":"Extreme precipitation in tropical squall lines","date_updated":"2023-12-13T13:06:40Z","day":"01","publication_identifier":{"eissn":["1942-2466"]},"publication":"Journal of Advances in Modeling Earth Systems","date_published":"2023-10-01T00:00:00Z","status":"public","abstract":[{"text":"Squall lines are substantially influenced by the interaction of low-level shear with cold pools associated with convective downdrafts. Beyond an optimal shear amplitude, squall lines tend to orient themselves at an angle with respect to the low-level shear. While the mechanisms behind squall line orientation seem to be increasingly well understood, uncertainties remain on the implications of this orientation. Roca and Fiolleau (2020, https://doi.org/10.1038/s43247-020-00015-4) show that long lived mesoscale convective systems, including squall lines, are disproportionately involved in rainfall extremes in the tropics. This article investigates the influence of the interaction between low-level shear and squall line outflow on squall line generated precipitation extrema in the tropics. Using a cloud resolving model, simulated squall lines in radiative convective equilibrium amid a shear-dominated regime (super optimal), a balanced regime (optimal), and an outflow dominated regime (suboptimal). Our results show that precipitation extremes in squall lines are 40% more intense in the case of optimal shear and remain 30% superior in the superoptimal regime relative to a disorganized case. With a theoretical scaling of precipitation extremes (C. Muller & Takayabu, 2020, https://doi.org/10.1088/1748-9326/ab7130), we show that the condensation rates control the amplification of precipitation extremes in tropical squall lines, mainly due to its change in vertical mass flux (dynamic component). The reduction of dilution by entrainment explains half of this change, consistent with Mulholland et al. (2021, https://doi.org/10.1175/jas-d-20-0299.1). The other half is explained by increased cloud-base velocity intensity in optimal and superoptimal squall lines.","lang":"eng"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"intvolume":" 15","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa_version":"Published Version","date_created":"2023-10-29T23:01:15Z","scopus_import":"1","type":"journal_article","volume":15,"quality_controlled":"1","project":[{"call_identifier":"H2020","grant_number":"805041","name":"organization of CLoUdS, and implications of Tropical cyclones and for the Energetics of the tropics, in current and waRming climate","_id":"629205d8-2b32-11ec-9570-e1356ff73576"}],"department":[{"_id":"CaMu"}],"publisher":"Wiley","publication_status":"published"},{"author":[{"id":"40876CD8-F248-11E8-B48F-1D18A9856A87","first_name":"Thomas A","last_name":"Henzinger","full_name":"Henzinger, Thomas A","orcid":"0000-0002-2985-7724"},{"id":"8121a2d0-dc85-11ea-9058-af578f3b4515","last_name":"Kueffner","first_name":"Konstantin","orcid":"0000-0001-8974-2542","full_name":"Kueffner, Konstantin"},{"full_name":"Mallik, Kaushik","orcid":"0000-0001-9864-7475","id":"0834ff3c-6d72-11ec-94e0-b5b0a4fb8598","last_name":"Mallik","first_name":"Kaushik"}],"month":"10","arxiv":1,"citation":{"ista":"Henzinger TA, Kueffner K, Mallik K. 2023. Monitoring algorithmic fairness under partial observations. 23rd International Conference on Runtime Verification. RV: Conference on Runtime Verification, LNCS, vol. 14245, 291–311.","apa":"Henzinger, T. A., Kueffner, K., & Mallik, K. (2023). Monitoring algorithmic fairness under partial observations. In 23rd International Conference on Runtime Verification (Vol. 14245, pp. 291–311). Thessaloniki, Greece: Springer Nature. https://doi.org/10.1007/978-3-031-44267-4_15","ama":"Henzinger TA, Kueffner K, Mallik K. Monitoring algorithmic fairness under partial observations. In: 23rd International Conference on Runtime Verification. Vol 14245. Springer Nature; 2023:291-311. doi:10.1007/978-3-031-44267-4_15","short":"T.A. Henzinger, K. Kueffner, K. Mallik, in:, 23rd International Conference on Runtime Verification, Springer Nature, 2023, pp. 291–311.","mla":"Henzinger, Thomas A., et al. “Monitoring Algorithmic Fairness under Partial Observations.” 23rd International Conference on Runtime Verification, vol. 14245, Springer Nature, 2023, pp. 291–311, doi:10.1007/978-3-031-44267-4_15.","chicago":"Henzinger, Thomas A, Konstantin Kueffner, and Kaushik Mallik. “Monitoring Algorithmic Fairness under Partial Observations.” In 23rd International Conference on Runtime Verification, 14245:291–311. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-44267-4_15.","ieee":"T. A. Henzinger, K. Kueffner, and K. Mallik, “Monitoring algorithmic fairness under partial observations,” in 23rd International Conference on Runtime Verification, Thessaloniki, Greece, 2023, vol. 14245, pp. 291–311."},"page":"291-311","language":[{"iso":"eng"}],"_id":"14454","acknowledgement":"This work is supported by the European Research Council under Grant No.: ERC-2020-AdG 101020093.","doi":"10.1007/978-3-031-44267-4_15","title":"Monitoring algorithmic fairness under partial observations","external_id":{"arxiv":["2308.00341"]},"day":"01","publication_identifier":{"issn":["0302-9743"],"isbn":["9783031442667"],"eissn":["1611-3349"]},"date_updated":"2023-10-31T11:48:20Z","conference":{"start_date":"2023-10-03","end_date":"2023-10-06","location":"Thessaloniki, Greece","name":"RV: Conference on Runtime Verification"},"ec_funded":1,"year":"2023","article_processing_charge":"No","oa":1,"oa_version":"Preprint","scopus_import":"1","alternative_title":["LNCS"],"date_created":"2023-10-29T23:01:15Z","abstract":[{"text":"As AI and machine-learned software are used increasingly for making decisions that affect humans, it is imperative that they remain fair and unbiased in their decisions. To complement design-time bias mitigation measures, runtime verification techniques have been introduced recently to monitor the algorithmic fairness of deployed systems. Previous monitoring techniques assume full observability of the states of the (unknown) monitored system. Moreover, they can monitor only fairness properties that are specified as arithmetic expressions over the probabilities of different events. In this work, we extend fairness monitoring to systems modeled as partially observed Markov chains (POMC), and to specifications containing arithmetic expressions over the expected values of numerical functions on event sequences. The only assumptions we make are that the underlying POMC is aperiodic and starts in the stationary distribution, with a bound on its mixing time being known. These assumptions enable us to estimate a given property for the entire distribution of possible executions of the monitored POMC, by observing only a single execution. Our monitors observe a long run of the system and, after each new observation, output updated PAC-estimates of how fair or biased the system is. The monitors are computationally lightweight and, using a prototype implementation, we demonstrate their effectiveness on several real-world examples.","lang":"eng"}],"publication":"23rd International Conference on Runtime Verification","status":"public","date_published":"2023-10-01T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","intvolume":" 14245","department":[{"_id":"ToHe"}],"quality_controlled":"1","project":[{"_id":"62781420-2b32-11ec-9570-8d9b63373d4d","name":"Vigilant Algorithmic Monitoring of Software","grant_number":"101020093","call_identifier":"H2020"}],"publication_status":"published","publisher":"Springer Nature","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2308.00341","open_access":"1"}],"type":"conference","volume":14245},{"publisher":"Frontiers","publication_status":"published","quality_controlled":"1","pmid":1,"department":[{"_id":"GaNo"}],"type":"journal_article","volume":14,"date_created":"2023-10-29T23:01:16Z","scopus_import":"1","oa_version":"Published Version","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"intvolume":" 14","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication":"Frontiers in Psychiatry","date_published":"2023-10-03T00:00:00Z","status":"public","date_updated":"2023-12-13T13:06:07Z","day":"03","publication_identifier":{"eissn":["1664-0640"]},"external_id":{"isi":["001084841700001"],"pmid":["37854442"]},"isi":1,"doi":"10.3389/fpsyt.2023.1287879","title":"Tempering expectations: Considerations on the current state of stem cells therapy for autism treatment","oa":1,"article_processing_charge":"Yes","year":"2023","has_accepted_license":"1","ddc":["570"],"citation":{"chicago":"Narzisi, Antonio, Alycia Halladay, Gabriele Masi, Gaia Novarino, and Catherine Lord. “Tempering Expectations: Considerations on the Current State of Stem Cells Therapy for Autism Treatment.” Frontiers in Psychiatry. Frontiers, 2023. https://doi.org/10.3389/fpsyt.2023.1287879.","ieee":"A. Narzisi, A. Halladay, G. Masi, G. Novarino, and C. Lord, “Tempering expectations: Considerations on the current state of stem cells therapy for autism treatment,” Frontiers in Psychiatry, vol. 14. Frontiers, 2023.","short":"A. Narzisi, A. Halladay, G. Masi, G. Novarino, C. Lord, Frontiers in Psychiatry 14 (2023).","mla":"Narzisi, Antonio, et al. “Tempering Expectations: Considerations on the Current State of Stem Cells Therapy for Autism Treatment.” Frontiers in Psychiatry, vol. 14, 1287879, Frontiers, 2023, doi:10.3389/fpsyt.2023.1287879.","ama":"Narzisi A, Halladay A, Masi G, Novarino G, Lord C. Tempering expectations: Considerations on the current state of stem cells therapy for autism treatment. Frontiers in Psychiatry. 2023;14. doi:10.3389/fpsyt.2023.1287879","ista":"Narzisi A, Halladay A, Masi G, Novarino G, Lord C. 2023. Tempering expectations: Considerations on the current state of stem cells therapy for autism treatment. Frontiers in Psychiatry. 14, 1287879.","apa":"Narzisi, A., Halladay, A., Masi, G., Novarino, G., & Lord, C. (2023). Tempering expectations: Considerations on the current state of stem cells therapy for autism treatment. Frontiers in Psychiatry. Frontiers. https://doi.org/10.3389/fpsyt.2023.1287879"},"article_type":"letter_note","file":[{"content_type":"application/pdf","creator":"dernst","checksum":"0a76373e9a4c0fc199f80380de257e86","relation":"main_file","file_name":"2023_FrontiersPsychiatry_Narzisi.pdf","success":1,"file_id":"14468","file_size":147878,"date_updated":"2023-10-30T12:48:40Z","date_created":"2023-10-30T12:48:40Z","access_level":"open_access"}],"author":[{"last_name":"Narzisi","first_name":"Antonio","full_name":"Narzisi, Antonio"},{"full_name":"Halladay, Alycia","first_name":"Alycia","last_name":"Halladay"},{"full_name":"Masi, Gabriele","first_name":"Gabriele","last_name":"Masi"},{"orcid":"0000-0002-7673-7178","full_name":"Novarino, Gaia","id":"3E57A680-F248-11E8-B48F-1D18A9856A87","last_name":"Novarino","first_name":"Gaia"},{"full_name":"Lord, Catherine","last_name":"Lord","first_name":"Catherine"}],"article_number":"1287879","month":"10","file_date_updated":"2023-10-30T12:48:40Z","language":[{"iso":"eng"}],"_id":"14455","acknowledgement":"The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This work has been partially supported by Italian Ministry of Health Grant RC2023 (and the 5 × 1,000 voluntary contributions). The authors thank the children and their families with whom they work daily."},{"oa_version":"Preprint","date_created":"2023-10-29T23:01:16Z","alternative_title":["LNCS"],"scopus_import":"1","date_published":"2023-09-21T00:00:00Z","status":"public","publication":"24th International Symposium on Fundamentals of Computation Theory","abstract":[{"text":"In this paper, we present novel algorithms that efficiently compute a shortest reconfiguration sequence between two given dominating sets in trees and interval graphs under the TOKEN SLIDING model. In this problem, a graph is provided along with its two dominating sets, which can be imagined as tokens placed on vertices. The objective is to find a shortest sequence of dominating sets that transforms one set into the other, with each set in the sequence resulting from sliding a single token in the previous set. While identifying any sequence has been well studied, our work presents the first polynomial algorithms for this optimization variant in the context of dominating sets.","lang":"eng"}],"intvolume":" 14292","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","quality_controlled":"1","department":[{"_id":"KrCh"}],"publisher":"Springer Nature","publication_status":"published","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2307.10847","open_access":"1"}],"volume":14292,"type":"conference","month":"09","author":[{"first_name":"Jan Matyáš","last_name":"Křišťan","full_name":"Křišťan, Jan Matyáš"},{"full_name":"Svoboda, Jakub","orcid":"0000-0002-1419-3267","first_name":"Jakub","last_name":"Svoboda","id":"130759D2-D7DD-11E9-87D2-DE0DE6697425"}],"arxiv":1,"citation":{"ieee":"J. M. Křišťan and J. Svoboda, “Shortest dominating set reconfiguration under token sliding,” in 24th International Symposium on Fundamentals of Computation Theory, Trier, Germany, 2023, vol. 14292, pp. 333–347.","chicago":"Křišťan, Jan Matyáš, and Jakub Svoboda. “Shortest Dominating Set Reconfiguration under Token Sliding.” In 24th International Symposium on Fundamentals of Computation Theory, 14292:333–47. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-43587-4_24.","mla":"Křišťan, Jan Matyáš, and Jakub Svoboda. “Shortest Dominating Set Reconfiguration under Token Sliding.” 24th International Symposium on Fundamentals of Computation Theory, vol. 14292, Springer Nature, 2023, pp. 333–47, doi:10.1007/978-3-031-43587-4_24.","short":"J.M. Křišťan, J. Svoboda, in:, 24th International Symposium on Fundamentals of Computation Theory, Springer Nature, 2023, pp. 333–347.","ama":"Křišťan JM, Svoboda J. Shortest dominating set reconfiguration under token sliding. In: 24th International Symposium on Fundamentals of Computation Theory. Vol 14292. Springer Nature; 2023:333-347. doi:10.1007/978-3-031-43587-4_24","apa":"Křišťan, J. M., & Svoboda, J. (2023). Shortest dominating set reconfiguration under token sliding. In 24th International Symposium on Fundamentals of Computation Theory (Vol. 14292, pp. 333–347). Trier, Germany: Springer Nature. https://doi.org/10.1007/978-3-031-43587-4_24","ista":"Křišťan JM, Svoboda J. 2023. Shortest dominating set reconfiguration under token sliding. 24th International Symposium on Fundamentals of Computation Theory. FCT: Fundamentals of Computation Theory, LNCS, vol. 14292, 333–347."},"page":"333-347","language":[{"iso":"eng"}],"_id":"14456","external_id":{"arxiv":["2307.10847"]},"title":"Shortest dominating set reconfiguration under token sliding","doi":"10.1007/978-3-031-43587-4_24","date_updated":"2024-01-22T08:10:49Z","publication_identifier":{"eissn":["1611-3349"],"isbn":["9783031435867"],"issn":["0302-9743"]},"day":"21","year":"2023","related_material":{"link":[{"url":"https://doi.org/10.1007/978-3-031-43587-4_31","relation":"erratum"}]},"conference":{"end_date":"2023-09-21","start_date":"2023-09-18","name":"FCT: Fundamentals of Computation Theory","location":"Trier, Germany"},"oa":1,"article_processing_charge":"No"},{"volume":14168,"type":"conference","main_file_link":[{"url":"https://eprint.iacr.org/2023/1017","open_access":"1"}],"publication_status":"published","publisher":"Springer Nature","department":[{"_id":"KrPi"}],"quality_controlled":"1","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","intvolume":" 14168","abstract":[{"text":"Threshold secret sharing allows a dealer to split a secret s into n shares, such that any t shares allow for reconstructing s, but no t-1 shares reveal any information about s. Leakage-resilient secret sharing requires that the secret remains hidden, even when an adversary additionally obtains a limited amount of leakage from every share. Benhamouda et al. (CRYPTO’18) proved that Shamir’s secret sharing scheme is one bit leakage-resilient for reconstruction threshold t≥0.85n and conjectured that the same holds for t = c.n for any constant 0≤c≤1. Nielsen and Simkin (EUROCRYPT’20) showed that this is the best one can hope for by proving that Shamir’s scheme is not secure against one-bit leakage when t0c.n/log(n).\r\nIn this work, we strengthen the lower bound of Nielsen and Simkin. We consider noisy leakage-resilience, where a random subset of leakages is replaced by uniformly random noise. We prove a lower bound for Shamir’s secret sharing, similar to that of Nielsen and Simkin, which holds even when a constant fraction of leakages is replaced by random noise. To this end, we first prove a lower bound on the share size of any noisy-leakage-resilient sharing scheme. We then use this lower bound to show that there exist universal constants c1, c2, such that for sufficiently large n it holds that Shamir’s secret sharing scheme is not noisy-leakage-resilient for t≤c1.n/log(n), even when a c2 fraction of leakages are replaced by random noise.\r\n\r\n\r\n\r\n","lang":"eng"}],"date_published":"2023-10-01T00:00:00Z","status":"public","publication":"8th International Conference on Cryptology and Information Security in Latin America","alternative_title":["LNCS"],"scopus_import":"1","date_created":"2023-10-29T23:01:16Z","oa_version":"Preprint","oa":1,"article_processing_charge":"No","conference":{"end_date":"2023-10-06","start_date":"2023-10-03","name":"LATINCRYPT: Conference on Cryptology and Information Security in Latin America","location":"Quito, Ecuador"},"year":"2023","publication_identifier":{"eissn":["1611-3349"],"isbn":["9783031444685"],"issn":["0302-9743"]},"day":"01","date_updated":"2023-10-31T11:43:12Z","title":"Stronger lower bounds for leakage-resilient secret sharing","doi":"10.1007/978-3-031-44469-2_11","_id":"14457","language":[{"iso":"eng"}],"page":"215-228","citation":{"ieee":"C. Hoffmann and M. Simkin, “Stronger lower bounds for leakage-resilient secret sharing,” in 8th International Conference on Cryptology and Information Security in Latin America, Quito, Ecuador, 2023, vol. 14168, pp. 215–228.","chicago":"Hoffmann, Charlotte, and Mark Simkin. “Stronger Lower Bounds for Leakage-Resilient Secret Sharing.” In 8th International Conference on Cryptology and Information Security in Latin America, 14168:215–28. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-44469-2_11.","short":"C. Hoffmann, M. Simkin, in:, 8th International Conference on Cryptology and Information Security in Latin America, Springer Nature, 2023, pp. 215–228.","mla":"Hoffmann, Charlotte, and Mark Simkin. “Stronger Lower Bounds for Leakage-Resilient Secret Sharing.” 8th International Conference on Cryptology and Information Security in Latin America, vol. 14168, Springer Nature, 2023, pp. 215–28, doi:10.1007/978-3-031-44469-2_11.","ama":"Hoffmann C, Simkin M. Stronger lower bounds for leakage-resilient secret sharing. In: 8th International Conference on Cryptology and Information Security in Latin America. Vol 14168. Springer Nature; 2023:215-228. doi:10.1007/978-3-031-44469-2_11","apa":"Hoffmann, C., & Simkin, M. (2023). Stronger lower bounds for leakage-resilient secret sharing. In 8th International Conference on Cryptology and Information Security in Latin America (Vol. 14168, pp. 215–228). Quito, Ecuador: Springer Nature. https://doi.org/10.1007/978-3-031-44469-2_11","ista":"Hoffmann C, Simkin M. 2023. Stronger lower bounds for leakage-resilient secret sharing. 8th International Conference on Cryptology and Information Security in Latin America. LATINCRYPT: Conference on Cryptology and Information Security in Latin America, LNCS, vol. 14168, 215–228."},"month":"10","author":[{"full_name":"Hoffmann, Charlotte","orcid":"0000-0003-2027-5549","id":"0f78d746-dc7d-11ea-9b2f-83f92091afe7","first_name":"Charlotte","last_name":"Hoffmann"},{"last_name":"Simkin","first_name":"Mark","full_name":"Simkin, Mark"}]},{"year":"2023","ec_funded":1,"conference":{"end_date":"2023-07-29","start_date":"2023-07-23","name":"ICML: International Conference on Machine Learning","location":"Honolulu, Hawaii, HI, United States"},"article_processing_charge":"No","oa":1,"external_id":{"arxiv":["2301.00774"]},"title":"SparseGPT: Massive language models can be accurately pruned in one-shot","date_updated":"2023-10-31T09:59:42Z","day":"30","publication_identifier":{"eissn":["2640-3498"]},"page":"10323-10337","language":[{"iso":"eng"}],"_id":"14458","acknowledgement":"The authors gratefully acknowledge funding from the European Research Council (ERC) under the European Union’s Horizon 2020 programme (grant agreement No. 805223 ScaleML), as well as experimental support from Eldar Kurtic, and from the IST Austria IT department, in particular Stefano Elefante, Andrei Hornoiu, and Alois Schloegl.","author":[{"id":"09a8f98d-ec99-11ea-ae11-c063a7b7fe5f","first_name":"Elias","last_name":"Frantar","full_name":"Frantar, Elias"},{"id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","last_name":"Alistarh","first_name":"Dan-Adrian","full_name":"Alistarh, Dan-Adrian","orcid":"0000-0003-3650-940X"}],"month":"07","citation":{"ama":"Frantar E, Alistarh D-A. SparseGPT: Massive language models can be accurately pruned in one-shot. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:10323-10337.","ista":"Frantar E, Alistarh D-A. 2023. SparseGPT: Massive language models can be accurately pruned in one-shot. Proceedings of the 40th International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 202, 10323–10337.","apa":"Frantar, E., & Alistarh, D.-A. (2023). SparseGPT: Massive language models can be accurately pruned in one-shot. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 10323–10337). Honolulu, Hawaii, HI, United States: ML Research Press.","chicago":"Frantar, Elias, and Dan-Adrian Alistarh. “SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot.” In Proceedings of the 40th International Conference on Machine Learning, 202:10323–37. ML Research Press, 2023.","ieee":"E. Frantar and D.-A. Alistarh, “SparseGPT: Massive language models can be accurately pruned in one-shot,” in Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, HI, United States, 2023, vol. 202, pp. 10323–10337.","short":"E. Frantar, D.-A. Alistarh, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 10323–10337.","mla":"Frantar, Elias, and Dan-Adrian Alistarh. “SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot.” Proceedings of the 40th International Conference on Machine Learning, vol. 202, ML Research Press, 2023, pp. 10323–37."},"arxiv":1,"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2301.00774"}],"type":"conference","volume":202,"quality_controlled":"1","project":[{"call_identifier":"H2020","grant_number":"805223","name":"Elastic Coordination for Scalable Machine Learning","_id":"268A44D6-B435-11E9-9278-68D0E5697425"}],"department":[{"_id":"DaAl"}],"publisher":"ML Research Press","acknowledged_ssus":[{"_id":"ScienComp"}],"publication_status":"published","publication":"Proceedings of the 40th International Conference on Machine Learning","status":"public","date_published":"2023-07-30T00:00:00Z","abstract":[{"text":"We show for the first time that large-scale generative pretrained transformer (GPT) family models can be pruned to at least 50% sparsity in one-shot, without any retraining, at minimal loss of accuracy. This is achieved via a new pruning method called SparseGPT, specifically designed to work efficiently and accurately on massive GPT-family models. We can execute SparseGPT on the largest available open-source models, OPT-175B and BLOOM-176B, in under 4.5 hours, and can reach 60% unstructured sparsity with negligible increase in perplexity: remarkably, more than 100 billion weights from these models can be ignored at inference time. SparseGPT generalizes to semi-structured (2:4 and 4:8) patterns, and is compatible with weight quantization approaches. The code is available at: https://github.com/IST-DASLab/sparsegpt.","lang":"eng"}],"intvolume":" 202","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa_version":"Preprint","date_created":"2023-10-29T23:01:16Z","scopus_import":"1","alternative_title":["PMLR"]},{"acknowledgement":"Aleksandr Shevchenko, Kevin Kogler and Marco Mondelli are supported by the 2019 Lopez-Loreta Prize. Hamed Hassani acknowledges the support by the NSF CIF award (1910056) and the NSF Institute for CORE Emerging Methods in Data Science (EnCORE).","language":[{"iso":"eng"}],"_id":"14459","page":"31151-31209","arxiv":1,"citation":{"ieee":"A. Shevchenko, K. Kögler, H. Hassani, and M. Mondelli, “Fundamental limits of two-layer autoencoders, and achieving them with gradient methods,” in Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, HI, United States, 2023, vol. 202, pp. 31151–31209.","chicago":"Shevchenko, Aleksandr, Kevin Kögler, Hamed Hassani, and Marco Mondelli. “Fundamental Limits of Two-Layer Autoencoders, and Achieving Them with Gradient Methods.” In Proceedings of the 40th International Conference on Machine Learning, 202:31151–209. ML Research Press, 2023.","short":"A. Shevchenko, K. Kögler, H. Hassani, M. Mondelli, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 31151–31209.","mla":"Shevchenko, Aleksandr, et al. “Fundamental Limits of Two-Layer Autoencoders, and Achieving Them with Gradient Methods.” Proceedings of the 40th International Conference on Machine Learning, vol. 202, ML Research Press, 2023, pp. 31151–209.","ama":"Shevchenko A, Kögler K, Hassani H, Mondelli M. Fundamental limits of two-layer autoencoders, and achieving them with gradient methods. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:31151-31209.","apa":"Shevchenko, A., Kögler, K., Hassani, H., & Mondelli, M. (2023). Fundamental limits of two-layer autoencoders, and achieving them with gradient methods. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 31151–31209). Honolulu, Hawaii, HI, United States: ML Research Press.","ista":"Shevchenko A, Kögler K, Hassani H, Mondelli M. 2023. Fundamental limits of two-layer autoencoders, and achieving them with gradient methods. Proceedings of the 40th International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 202, 31151–31209."},"month":"07","author":[{"last_name":"Shevchenko","first_name":"Aleksandr","id":"F2B06EC2-C99E-11E9-89F0-752EE6697425","full_name":"Shevchenko, Aleksandr"},{"id":"94ec913c-dc85-11ea-9058-e5051ab2428b","last_name":"Kögler","first_name":"Kevin","full_name":"Kögler, Kevin"},{"full_name":"Hassani, Hamed","last_name":"Hassani","first_name":"Hamed"},{"first_name":"Marco","last_name":"Mondelli","id":"27EB676C-8706-11E9-9510-7717E6697425","orcid":"0000-0002-3242-7020","full_name":"Mondelli, Marco"}],"oa":1,"article_processing_charge":"No","year":"2023","conference":{"location":"Honolulu, Hawaii, HI, United States","name":"ICML: International Conference on Machine Learning","start_date":"2023-07-23","end_date":"2023-07-29"},"date_updated":"2024-09-10T13:03:19Z","publication_identifier":{"eissn":["2640-3498"]},"day":"30","external_id":{"arxiv":["2212.13468"]},"title":"Fundamental limits of two-layer autoencoders, and achieving them with gradient methods","intvolume":" 202","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","status":"public","date_published":"2023-07-30T00:00:00Z","publication":"Proceedings of the 40th International Conference on Machine Learning","abstract":[{"text":"Autoencoders are a popular model in many branches of machine learning and lossy data compression. However, their fundamental limits, the performance of gradient methods and the features learnt during optimization remain poorly understood, even in the two-layer setting. In fact, earlier work has considered either linear autoencoders or specific training regimes (leading to vanishing or diverging compression rates). Our paper addresses this gap by focusing on non-linear two-layer autoencoders trained in the challenging proportional regime in which the input dimension scales linearly with the size of the representation. Our results characterize the minimizers of the population risk, and show that such minimizers are achieved by gradient methods; their structure is also unveiled, thus leading to a concise description of the features obtained via training. For the special case of a sign activation function, our analysis establishes the fundamental limits for the lossy compression of Gaussian sources via (shallow) autoencoders. Finally, while the results are proved for Gaussian data, numerical simulations on standard datasets display the universality of the theoretical predictions.","lang":"eng"}],"date_created":"2023-10-29T23:01:17Z","alternative_title":["PMLR"],"scopus_import":"1","oa_version":"Preprint","volume":202,"type":"conference","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2212.13468"}],"publisher":"ML Research Press","publication_status":"published","project":[{"_id":"059876FA-7A3F-11EA-A408-12923DDC885E","name":"Prix Lopez-Loretta 2019 - Marco Mondelli"}],"quality_controlled":"1","department":[{"_id":"MaMo"},{"_id":"DaAl"}]},{"department":[{"_id":"DaAl"}],"project":[{"_id":"268A44D6-B435-11E9-9278-68D0E5697425","name":"Elastic Coordination for Scalable Machine Learning","grant_number":"805223","call_identifier":"H2020"}],"quality_controlled":"1","publication_status":"published","publisher":"ML Research Press","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2302.04852","open_access":"1"}],"volume":202,"type":"conference","oa_version":"Preprint","alternative_title":["PMLR"],"scopus_import":"1","date_created":"2023-10-29T23:01:17Z","abstract":[{"text":"We provide an efficient implementation of the backpropagation algorithm, specialized to the case where the weights of the neural network being trained are sparse. Our algorithm is general, as it applies to arbitrary (unstructured) sparsity and common layer types (e.g., convolutional or linear). We provide a fast vectorized implementation on commodity CPUs, and show that it can yield speedups in end-to-end runtime experiments, both in transfer learning using already-sparsified networks, and in training sparse networks from scratch. Thus, our results provide the first support for sparse training on commodity hardware.","lang":"eng"}],"status":"public","date_published":"2023-07-30T00:00:00Z","publication":"Proceedings of the 40th International Conference on Machine Learning","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","intvolume":" 202","title":"SparseProp: Efficient sparse backpropagation for faster training of neural networks at the edge","external_id":{"arxiv":["2302.04852"]},"publication_identifier":{"eissn":["2640-3498"]},"day":"30","date_updated":"2023-10-31T09:33:51Z","conference":{"name":"ICML: International Conference on Machine Learning","location":"Honolulu, Hawaii, HI, United States","end_date":"2023-07-29","start_date":"2023-07-23"},"ec_funded":1,"year":"2023","article_processing_charge":"No","oa":1,"month":"07","author":[{"full_name":"Nikdan, Mahdi","first_name":"Mahdi","last_name":"Nikdan","id":"66374281-f394-11eb-9cf6-869147deecc0"},{"full_name":"Pegolotti, Tommaso","first_name":"Tommaso","last_name":"Pegolotti"},{"id":"f9a17499-f6e0-11ea-865d-fdf9a3f77117","last_name":"Iofinova","first_name":"Eugenia B","orcid":"0000-0002-7778-3221","full_name":"Iofinova, Eugenia B"},{"id":"47beb3a5-07b5-11eb-9b87-b108ec578218","last_name":"Kurtic","first_name":"Eldar","full_name":"Kurtic, Eldar"},{"first_name":"Dan-Adrian","last_name":"Alistarh","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-3650-940X","full_name":"Alistarh, Dan-Adrian"}],"arxiv":1,"citation":{"chicago":"Nikdan, Mahdi, Tommaso Pegolotti, Eugenia B Iofinova, Eldar Kurtic, and Dan-Adrian Alistarh. “SparseProp: Efficient Sparse Backpropagation for Faster Training of Neural Networks at the Edge.” In Proceedings of the 40th International Conference on Machine Learning, 202:26215–27. ML Research Press, 2023.","ieee":"M. Nikdan, T. Pegolotti, E. B. Iofinova, E. Kurtic, and D.-A. Alistarh, “SparseProp: Efficient sparse backpropagation for faster training of neural networks at the edge,” in Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, HI, United States, 2023, vol. 202, pp. 26215–26227.","short":"M. Nikdan, T. Pegolotti, E.B. Iofinova, E. Kurtic, D.-A. Alistarh, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 26215–26227.","mla":"Nikdan, Mahdi, et al. “SparseProp: Efficient Sparse Backpropagation for Faster Training of Neural Networks at the Edge.” Proceedings of the 40th International Conference on Machine Learning, vol. 202, ML Research Press, 2023, pp. 26215–27.","ama":"Nikdan M, Pegolotti T, Iofinova EB, Kurtic E, Alistarh D-A. SparseProp: Efficient sparse backpropagation for faster training of neural networks at the edge. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:26215-26227.","ista":"Nikdan M, Pegolotti T, Iofinova EB, Kurtic E, Alistarh D-A. 2023. SparseProp: Efficient sparse backpropagation for faster training of neural networks at the edge. Proceedings of the 40th International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 202, 26215–26227.","apa":"Nikdan, M., Pegolotti, T., Iofinova, E. B., Kurtic, E., & Alistarh, D.-A. (2023). SparseProp: Efficient sparse backpropagation for faster training of neural networks at the edge. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 26215–26227). Honolulu, Hawaii, HI, United States: ML Research Press."},"page":"26215-26227","acknowledgement":"We would like to thank Elias Frantar for his valuable assistance and support at the outset of this project, and the anonymous ICML and SNN reviewers for very constructive feedback. EI was supported in part by the FWF DK VGSCO, grant agreement number W1260-N35. DA acknowledges generous ERC support, via Starting Grant 805223 ScaleML. ","_id":"14460","language":[{"iso":"eng"}]}]