[{"date_created":"2023-02-10T13:47:56Z","arxiv":1,"day":"16","publication_status":"published","author":[{"last_name":"Amani","first_name":"Mohammad Hossein","full_name":"Amani, Mohammad Hossein"},{"last_name":"Bombari","id":"ca726dda-de17-11ea-bc14-f9da834f63aa","first_name":"Simone","full_name":"Bombari, Simone"},{"first_name":"Marco","id":"27EB676C-8706-11E9-9510-7717E6697425","full_name":"Mondelli, Marco","orcid":"0000-0002-3242-7020","last_name":"Mondelli"},{"last_name":"Pukdee","full_name":"Pukdee, Rattana","first_name":"Rattana"},{"first_name":"Stefano","full_name":"Rini, Stefano","last_name":"Rini"}],"conference":{"end_date":"2022-11-09","location":"Mumbai, India","name":"ITW: Information Theory Workshop","start_date":"2022-11-01"},"page":"588-593","department":[{"_id":"MaMo"}],"language":[{"iso":"eng"}],"year":"2022","external_id":{"arxiv":["2205.08199"]},"oa_version":"Preprint","article_type":"original","date_published":"2022-11-16T00:00:00Z","type":"journal_article","month":"11","oa":1,"quality_controlled":"1","article_processing_charge":"No","doi":"10.1109/ITW54588.2022.9965870","date_updated":"2023-12-18T11:31:47Z","publisher":"IEEE","publication":"IEEE Information Theory Workshop","publication_identifier":{"isbn":["9781665483414"]},"scopus_import":"1","citation":{"short":"M.H. Amani, S. Bombari, M. Mondelli, R. Pukdee, S. Rini, IEEE Information Theory Workshop (2022) 588–593.","ieee":"M. H. Amani, S. Bombari, M. Mondelli, R. Pukdee, and S. Rini, “Sharp asymptotics on the compression of two-layer neural networks,” <i>IEEE Information Theory Workshop</i>. IEEE, pp. 588–593, 2022.","apa":"Amani, M. H., Bombari, S., Mondelli, M., Pukdee, R., &#38; Rini, S. (2022). Sharp asymptotics on the compression of two-layer neural networks. <i>IEEE Information Theory Workshop</i>. Mumbai, India: IEEE. <a href=\"https://doi.org/10.1109/ITW54588.2022.9965870\">https://doi.org/10.1109/ITW54588.2022.9965870</a>","ista":"Amani MH, Bombari S, Mondelli M, Pukdee R, Rini S. 2022. Sharp asymptotics on the compression of two-layer neural networks. IEEE Information Theory Workshop., 588–593.","chicago":"Amani, Mohammad Hossein, Simone Bombari, Marco Mondelli, Rattana Pukdee, and Stefano Rini. “Sharp Asymptotics on the Compression of Two-Layer Neural Networks.” <i>IEEE Information Theory Workshop</i>. IEEE, 2022. <a href=\"https://doi.org/10.1109/ITW54588.2022.9965870\">https://doi.org/10.1109/ITW54588.2022.9965870</a>.","mla":"Amani, Mohammad Hossein, et al. “Sharp Asymptotics on the Compression of Two-Layer Neural Networks.” <i>IEEE Information Theory Workshop</i>, IEEE, 2022, pp. 588–93, doi:<a href=\"https://doi.org/10.1109/ITW54588.2022.9965870\">10.1109/ITW54588.2022.9965870</a>.","ama":"Amani MH, Bombari S, Mondelli M, Pukdee R, Rini S. Sharp asymptotics on the compression of two-layer neural networks. <i>IEEE Information Theory Workshop</i>. 2022:588-593. doi:<a href=\"https://doi.org/10.1109/ITW54588.2022.9965870\">10.1109/ITW54588.2022.9965870</a>"},"main_file_link":[{"url":" https://doi.org/10.48550/arXiv.2205.08199","open_access":"1"}],"status":"public","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","abstract":[{"text":"In this paper, we study the compression of a target two-layer neural network with N nodes into a compressed network with M<N nodes. More precisely, we consider the setting in which the weights of the target network are i.i.d. sub-Gaussian, and we minimize the population L_2 loss between the outputs of the target and of the compressed network, under the assumption of Gaussian inputs. By using tools from high-dimensional probability, we show that this non-convex problem can be simplified when the target network is sufficiently over-parameterized, and provide the error rate of this approximation as a function of the input dimension and N. In this mean-field limit, the simplified objective, as well as the optimal weights of the compressed network, does not depend on the realization of the target network, but only on expected scaling factors. Furthermore, for networks with ReLU activation, we conjecture that the optimum of the simplified optimization problem is achieved by taking weights on the Equiangular Tight Frame (ETF), while the scaling of the weights and the orientation of the ETF depend on the parameters of the target network. Numerical evidence is provided to support this conjecture.","lang":"eng"}],"title":"Sharp asymptotics on the compression of two-layer neural networks","_id":"12538"},{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","abstract":[{"lang":"eng","text":"We consider the problem of signal estimation in generalized linear models defined via rotationally invariant design matrices. Since these matrices can have an arbitrary spectral distribution, this model is well suited for capturing complex correlation structures which often arise in applications. We propose a novel family of approximate message passing (AMP) algorithms for signal estimation, and rigorously characterize their performance in the high-dimensional limit via a state evolution recursion. Our rotationally invariant AMP has complexity of the same order as the existing AMP derived under the restrictive assumption of a Gaussian design; our algorithm also recovers this existing AMP as a special case. Numerical results showcase a performance close to Vector AMP (which is conjectured to be Bayes-optimal in some settings), but obtained with a much lower complexity, as the proposed algorithm does not require a computationally expensive singular value decomposition."}],"title":"Estimation in rotationally invariant generalized linear models via approximate message passing","_id":"12540","acknowledgement":"The authors would like to thank the anonymous reviewers for their helpful comments. KK and MM were partially supported by the 2019 Lopez-Loreta Prize.","status":"public","intvolume":"       162","citation":{"short":"R. Venkataramanan, K. Kögler, M. Mondelli, in:, Proceedings of the 39th International Conference on Machine Learning, ML Research Press, 2022.","ieee":"R. Venkataramanan, K. Kögler, and M. Mondelli, “Estimation in rotationally invariant generalized linear models via approximate message passing,” in <i>Proceedings of the 39th International Conference on Machine Learning</i>, Baltimore, MD, United States, 2022, vol. 162.","ista":"Venkataramanan R, Kögler K, Mondelli M. 2022. Estimation in rotationally invariant generalized linear models via approximate message passing. Proceedings of the 39th International Conference on Machine Learning. ICML: International Conference on Machine Learning vol. 162, 22.","apa":"Venkataramanan, R., Kögler, K., &#38; Mondelli, M. (2022). Estimation in rotationally invariant generalized linear models via approximate message passing. In <i>Proceedings of the 39th International Conference on Machine Learning</i> (Vol. 162). Baltimore, MD, United States: ML Research Press.","chicago":"Venkataramanan, Ramji, Kevin Kögler, and Marco Mondelli. “Estimation in Rotationally Invariant Generalized Linear Models via Approximate Message Passing.” In <i>Proceedings of the 39th International Conference on Machine Learning</i>, Vol. 162. ML Research Press, 2022.","ama":"Venkataramanan R, Kögler K, Mondelli M. Estimation in rotationally invariant generalized linear models via approximate message passing. In: <i>Proceedings of the 39th International Conference on Machine Learning</i>. Vol 162. ML Research Press; 2022.","mla":"Venkataramanan, Ramji, et al. “Estimation in Rotationally Invariant Generalized Linear Models via Approximate Message Passing.” <i>Proceedings of the 39th International Conference on Machine Learning</i>, vol. 162, 22, ML Research Press, 2022."},"has_accepted_license":"1","file_date_updated":"2023-02-13T10:53:11Z","article_processing_charge":"No","publisher":"ML Research Press","date_updated":"2024-09-10T13:03:17Z","publication":"Proceedings of the 39th International Conference on Machine Learning","oa":1,"quality_controlled":"1","file":[{"checksum":"67436eb0a660789514cdf9db79e84683","access_level":"open_access","file_name":"2022_PMLR_Venkataramanan.pdf","success":1,"file_size":2341343,"date_updated":"2023-02-13T10:53:11Z","file_id":"12547","date_created":"2023-02-13T10:53:11Z","content_type":"application/pdf","relation":"main_file","creator":"dernst"}],"article_number":"22","date_published":"2022-01-01T00:00:00Z","project":[{"_id":"059876FA-7A3F-11EA-A408-12923DDC885E","name":"Prix Lopez-Loretta 2019 - Marco Mondelli"}],"type":"conference","volume":162,"oa_version":"Published Version","ddc":["000"],"year":"2022","language":[{"iso":"eng"}],"department":[{"_id":"MaMo"}],"author":[{"first_name":"Ramji","full_name":"Venkataramanan, Ramji","last_name":"Venkataramanan"},{"last_name":"Kögler","full_name":"Kögler, Kevin","first_name":"Kevin","id":"94ec913c-dc85-11ea-9058-e5051ab2428b"},{"first_name":"Marco","id":"27EB676C-8706-11E9-9510-7717E6697425","full_name":"Mondelli, Marco","last_name":"Mondelli","orcid":"0000-0002-3242-7020"}],"conference":{"location":"Baltimore, MD, United States","end_date":"2022-07-23","start_date":"2022-07-17","name":"ICML: International Conference on Machine Learning"},"date_created":"2023-02-10T13:49:04Z","publication_status":"published"},{"scopus_import":"1","publication_identifier":{"eissn":["2374-3468"],"isbn":["1577358767"]},"issue":"9","title":"Risk-aware stochastic shortest path","_id":"12568","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","abstract":[{"lang":"eng","text":"We treat the problem of risk-aware control for stochastic shortest path (SSP) on Markov decision processes (MDP). Typically, expectation is considered for SSP, which however is oblivious to the incurred risk. We present an alternative view, instead optimizing conditional value-at-risk (CVaR), an established risk measure. We treat both Markov chains as well as MDP and introduce, through novel insights, two algorithms, based on linear programming and value iteration, respectively. Both algorithms offer precise and provably correct solutions. Evaluation of our prototype implementation shows that risk-aware control is feasible on several moderately sized models."}],"intvolume":"        36","citation":{"chicago":"Meggendorfer, Tobias. “Risk-Aware Stochastic Shortest Path.” In <i>Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022</i>, 36:9858–67. Association for the Advancement of Artificial Intelligence, 2022. <a href=\"https://doi.org/10.1609/aaai.v36i9.21222\">https://doi.org/10.1609/aaai.v36i9.21222</a>.","ama":"Meggendorfer T. Risk-aware stochastic shortest path. In: <i>Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022</i>. Vol 36. Association for the Advancement of Artificial Intelligence; 2022:9858-9867. doi:<a href=\"https://doi.org/10.1609/aaai.v36i9.21222\">10.1609/aaai.v36i9.21222</a>","mla":"Meggendorfer, Tobias. “Risk-Aware Stochastic Shortest Path.” <i>Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022</i>, vol. 36, no. 9, Association for the Advancement of Artificial Intelligence, 2022, pp. 9858–67, doi:<a href=\"https://doi.org/10.1609/aaai.v36i9.21222\">10.1609/aaai.v36i9.21222</a>.","short":"T. Meggendorfer, in:, Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022, Association for the Advancement of Artificial Intelligence, 2022, pp. 9858–9867.","ieee":"T. Meggendorfer, “Risk-aware stochastic shortest path,” in <i>Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022</i>, Virtual, 2022, vol. 36, no. 9, pp. 9858–9867.","ista":"Meggendorfer T. 2022. Risk-aware stochastic shortest path. Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022. Conference on Artificial Intelligence vol. 36, 9858–9867.","apa":"Meggendorfer, T. (2022). Risk-aware stochastic shortest path. In <i>Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022</i> (Vol. 36, pp. 9858–9867). Virtual: Association for the Advancement of Artificial Intelligence. <a href=\"https://doi.org/10.1609/aaai.v36i9.21222\">https://doi.org/10.1609/aaai.v36i9.21222</a>"},"main_file_link":[{"url":" https://doi.org/10.48550/arXiv.2203.01640","open_access":"1"}],"status":"public","department":[{"_id":"KrCh"}],"year":"2022","language":[{"iso":"eng"}],"day":"28","publication_status":"published","arxiv":1,"date_created":"2023-02-19T23:00:56Z","conference":{"end_date":"2022-03-01","location":"Virtual","name":"Conference on Artificial Intelligence","start_date":"2022-02-22"},"page":"9858-9867","author":[{"id":"b21b0c15-30a2-11eb-80dc-f13ca25802e1","first_name":"Tobias","full_name":"Meggendorfer, Tobias","last_name":"Meggendorfer","orcid":"0000-0002-1712-2165"}],"oa":1,"quality_controlled":"1","month":"06","publisher":"Association for the Advancement of Artificial Intelligence","doi":"10.1609/aaai.v36i9.21222","date_updated":"2023-02-20T07:19:12Z","publication":"Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022","article_processing_charge":"No","external_id":{"arxiv":["2203.01640"]},"oa_version":"Preprint","date_published":"2022-06-28T00:00:00Z","type":"conference","volume":36},{"language":[{"iso":"eng"}],"year":"2022","ddc":["004"],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"department":[{"_id":"ChLa"}],"file_date_updated":"2023-02-20T08:21:35Z","author":[{"full_name":"Scott, Jonathan A","id":"e499926b-f6e0-11ea-865d-9c63db0031e8","first_name":"Jonathan A","last_name":"Scott"},{"last_name":"Yeo","id":"2D82B818-F248-11E8-B48F-1D18A9856A87","first_name":"Michelle X","full_name":"Yeo, Michelle X"},{"first_name":"Christoph","id":"40C20FD2-F248-11E8-B48F-1D18A9856A87","full_name":"Lampert, Christoph","orcid":"0000-0001-8622-7887","last_name":"Lampert"}],"publication_status":"submitted","day":"12","date_created":"2023-02-20T08:21:50Z","arxiv":1,"_id":"12660","publication":"arXiv","title":"Cross-client Label Propagation for transductive federated learning","doi":"10.48550/arXiv.2210.06434","date_updated":"2023-02-21T08:20:18Z","abstract":[{"text":"We present Cross-Client Label Propagation(XCLP), a new method for transductive federated learning. XCLP estimates a data graph jointly from the data of multiple clients and computes labels for the unlabeled data by propagating label information across the graph. To avoid clients having to share their data with anyone, XCLP employs two cryptographically secure protocols: secure Hamming distance computation and secure summation. We demonstrate two distinct applications of XCLP within federated learning. In the first, we use it in a one-shot way to predict labels for unseen test points. In the second, we use it to repeatedly pseudo-label unlabeled training data in a federated semi-supervised setting. Experiments on both real federated and standard benchmark datasets show that in both applications XCLP achieves higher classification accuracy than alternative approaches.","lang":"eng"}],"article_processing_charge":"No","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_number":"2210.06434","file":[{"file_size":291893,"date_updated":"2023-02-20T08:21:35Z","checksum":"7ab20543fd4393f14fb857ce2e4f03c6","file_name":"2210.06434.pdf","access_level":"open_access","success":1,"creator":"chl","relation":"main_file","file_id":"12661","date_created":"2023-02-20T08:21:35Z","content_type":"application/pdf"}],"oa":1,"month":"10","status":"public","type":"preprint","date_published":"2022-10-12T00:00:00Z","has_accepted_license":"1","citation":{"chicago":"Scott, Jonathan A, Michelle X Yeo, and Christoph Lampert. “Cross-Client Label Propagation for Transductive Federated Learning.” <i>ArXiv</i>, n.d. <a href=\"https://doi.org/10.48550/arXiv.2210.06434\">https://doi.org/10.48550/arXiv.2210.06434</a>.","ama":"Scott JA, Yeo MX, Lampert C. Cross-client Label Propagation for transductive federated learning. <i>arXiv</i>. doi:<a href=\"https://doi.org/10.48550/arXiv.2210.06434\">10.48550/arXiv.2210.06434</a>","mla":"Scott, Jonathan A., et al. “Cross-Client Label Propagation for Transductive Federated Learning.” <i>ArXiv</i>, 2210.06434, doi:<a href=\"https://doi.org/10.48550/arXiv.2210.06434\">10.48550/arXiv.2210.06434</a>.","ieee":"J. A. Scott, M. X. Yeo, and C. Lampert, “Cross-client Label Propagation for transductive federated learning,” <i>arXiv</i>. .","short":"J.A. Scott, M.X. Yeo, C. Lampert, ArXiv (n.d.).","ista":"Scott JA, Yeo MX, Lampert C. Cross-client Label Propagation for transductive federated learning. arXiv, 2210.06434.","apa":"Scott, J. A., Yeo, M. X., &#38; Lampert, C. (n.d.). Cross-client Label Propagation for transductive federated learning. <i>arXiv</i>. <a href=\"https://doi.org/10.48550/arXiv.2210.06434\">https://doi.org/10.48550/arXiv.2210.06434</a>"},"oa_version":"Preprint","external_id":{"arxiv":["2210.06434"]}},{"article_number":"2208.13499","oa":1,"month":"08","_id":"12662","publication":"arXiv","title":"Generalization in Multi-objective machine learning","doi":"10.48550/arXiv.2208.13499","date_updated":"2023-02-21T08:24:55Z","abstract":[{"text":"Modern machine learning tasks often require considering not just one but multiple objectives. For example, besides the prediction quality, this could be the efficiency, robustness or fairness of the learned models, or any of their combinations. Multi-objective learning offers a natural framework for handling such problems without having to commit to early trade-offs. Surprisingly, statistical learning theory so far offers almost no insight into the generalization properties of multi-objective learning. In this work, we make first steps to fill this gap: we establish foundational generalization bounds for the multi-objective setting as well as generalization and excess bounds for learning with scalarizations. We also provide the first theoretical analysis of the relation between the Pareto-optimal sets of the true objectives and the Pareto-optimal sets of their empirical approximations from training data. In particular, we show a surprising asymmetry: all Pareto-optimal solutions can be approximated by empirically Pareto-optimal ones, but not vice versa.","lang":"eng"}],"article_processing_charge":"No","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","main_file_link":[{"open_access":"1","url":" https://doi.org/10.48550/arXiv.2208.13499"}],"has_accepted_license":"1","citation":{"ieee":"P. Súkeník and C. Lampert, “Generalization in Multi-objective machine learning,” <i>arXiv</i>. .","short":"P. Súkeník, C. Lampert, ArXiv (n.d.).","apa":"Súkeník, P., &#38; Lampert, C. (n.d.). Generalization in Multi-objective machine learning. <i>arXiv</i>. <a href=\"https://doi.org/10.48550/arXiv.2208.13499\">https://doi.org/10.48550/arXiv.2208.13499</a>","ista":"Súkeník P, Lampert C. Generalization in Multi-objective machine learning. arXiv, 2208.13499.","chicago":"Súkeník, Peter, and Christoph Lampert. “Generalization in Multi-Objective Machine Learning.” <i>ArXiv</i>, n.d. <a href=\"https://doi.org/10.48550/arXiv.2208.13499\">https://doi.org/10.48550/arXiv.2208.13499</a>.","mla":"Súkeník, Peter, and Christoph Lampert. “Generalization in Multi-Objective Machine Learning.” <i>ArXiv</i>, 2208.13499, doi:<a href=\"https://doi.org/10.48550/arXiv.2208.13499\">10.48550/arXiv.2208.13499</a>.","ama":"Súkeník P, Lampert C. Generalization in Multi-objective machine learning. <i>arXiv</i>. doi:<a href=\"https://doi.org/10.48550/arXiv.2208.13499\">10.48550/arXiv.2208.13499</a>"},"oa_version":"Preprint","external_id":{"arxiv":["2208.13499"]},"status":"public","date_published":"2022-08-29T00:00:00Z","type":"preprint","department":[{"_id":"ChLa"}],"language":[{"iso":"eng"}],"year":"2022","ddc":["004"],"publication_status":"submitted","day":"29","arxiv":1,"date_created":"2023-02-20T08:23:06Z","author":[{"last_name":"Súkeník","full_name":"Súkeník, Peter","id":"d64d6a8d-eb8e-11eb-b029-96fd216dec3c","first_name":"Peter"},{"full_name":"Lampert, Christoph","id":"40C20FD2-F248-11E8-B48F-1D18A9856A87","first_name":"Christoph","last_name":"Lampert","orcid":"0000-0001-8622-7887"}]},{"scopus_import":"1","issue":"12","publication_identifier":{"issn":["1672-9072"],"eissn":["1744-7909"]},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","abstract":[{"text":"DNA methylation plays essential homeostatic functions in eukaryotic genomes. In animals, DNA methylation is also developmentally regulated and, in turn, regulates development. In the past two decades, huge research effort has endorsed the understanding that DNA methylation plays a similar role in plant development, especially during sexual reproduction. The power of whole-genome sequencing and cell isolation techniques, as well as bioinformatics tools, have enabled recent studies to reveal dynamic changes in DNA methylation during germline development. Furthermore, the combination of these technological advances with genetics, developmental biology and cell biology tools has revealed functional methylation reprogramming events that control gene and transposon activities in flowering plant germlines. In this review, we discuss the major advances in our knowledge of DNA methylation dynamics during male and female germline development in flowering plants.","lang":"eng"}],"title":"DNA methylation dynamics during germline development","_id":"12670","pmid":1,"status":"public","citation":{"chicago":"He, Shengbo, and Xiaoqi Feng. “DNA Methylation Dynamics during Germline Development.” <i>Journal of Integrative Plant Biology</i>. Wiley, 2022. <a href=\"https://doi.org/10.1111/jipb.13422\">https://doi.org/10.1111/jipb.13422</a>.","ama":"He S, Feng X. DNA methylation dynamics during germline development. <i>Journal of Integrative Plant Biology</i>. 2022;64(12):2240-2251. doi:<a href=\"https://doi.org/10.1111/jipb.13422\">10.1111/jipb.13422</a>","mla":"He, Shengbo, and Xiaoqi Feng. “DNA Methylation Dynamics during Germline Development.” <i>Journal of Integrative Plant Biology</i>, vol. 64, no. 12, Wiley, 2022, pp. 2240–51, doi:<a href=\"https://doi.org/10.1111/jipb.13422\">10.1111/jipb.13422</a>.","ieee":"S. He and X. Feng, “DNA methylation dynamics during germline development,” <i>Journal of Integrative Plant Biology</i>, vol. 64, no. 12. Wiley, pp. 2240–2251, 2022.","short":"S. He, X. Feng, Journal of Integrative Plant Biology 64 (2022) 2240–2251.","ista":"He S, Feng X. 2022. DNA methylation dynamics during germline development. Journal of Integrative Plant Biology. 64(12), 2240–2251.","apa":"He, S., &#38; Feng, X. (2022). DNA methylation dynamics during germline development. <i>Journal of Integrative Plant Biology</i>. Wiley. <a href=\"https://doi.org/10.1111/jipb.13422\">https://doi.org/10.1111/jipb.13422</a>"},"intvolume":"        64","main_file_link":[{"url":"https://doi.org/10.1111/jipb.13422","open_access":"1"}],"year":"2022","language":[{"iso":"eng"}],"department":[{"_id":"XiFe"}],"author":[{"full_name":"He, Shengbo","first_name":"Shengbo","last_name":"He"},{"orcid":"0000-0002-4008-1234","last_name":"Feng","first_name":"Xiaoqi","id":"e0164712-22ee-11ed-b12a-d80fcdf35958","full_name":"Feng, Xiaoqi"}],"keyword":["Plant Science","General Biochemistry","Genetics and Molecular Biology","Biochemistry"],"page":"2240-2251","date_created":"2023-02-23T09:15:57Z","day":"07","publication_status":"published","article_processing_charge":"No","date_updated":"2023-05-08T10:59:00Z","publisher":"Wiley","doi":"10.1111/jipb.13422","publication":"Journal of Integrative Plant Biology","month":"12","oa":1,"quality_controlled":"1","extern":"1","type":"journal_article","date_published":"2022-12-07T00:00:00Z","volume":64,"oa_version":"Published Version","article_type":"review","external_id":{"pmid":["36478632"]}},{"author":[{"first_name":"Toby","full_name":"Buttress, Toby","last_name":"Buttress"},{"last_name":"He","first_name":"Shengbo","full_name":"He, Shengbo"},{"last_name":"Wang","full_name":"Wang, Liang","first_name":"Liang"},{"full_name":"Zhou, Shaoli","first_name":"Shaoli","last_name":"Zhou"},{"first_name":"Gerhard","full_name":"Saalbach, Gerhard","last_name":"Saalbach"},{"last_name":"Vickers","first_name":"Martin","full_name":"Vickers, Martin"},{"first_name":"Guohong","full_name":"Li, Guohong","last_name":"Li"},{"last_name":"Li","full_name":"Li, Pilong","first_name":"Pilong"},{"orcid":"0000-0002-4008-1234","last_name":"Feng","first_name":"Xiaoqi","id":"e0164712-22ee-11ed-b12a-d80fcdf35958","full_name":"Feng, Xiaoqi"}],"page":"614-622","date_created":"2023-02-23T09:17:05Z","day":"17","publication_status":"published","year":"2022","language":[{"iso":"eng"}],"department":[{"_id":"XiFe"}],"type":"journal_article","date_published":"2022-11-17T00:00:00Z","volume":611,"external_id":{"pmid":["36323776"]},"oa_version":"Published Version","article_type":"original","article_processing_charge":"No","date_updated":"2023-05-08T10:59:22Z","publisher":"Springer Nature","doi":"10.1038/s41586-022-05386-6","publication":"Nature","month":"11","quality_controlled":"1","oa":1,"extern":"1","issue":"7936","publication_identifier":{"issn":["0028-0836"],"eissn":["1476-4687"]},"scopus_import":"1","status":"public","citation":{"mla":"Buttress, Toby, et al. “Histone H2B.8 Compacts Flowering Plant Sperm through Chromatin Phase Separation.” <i>Nature</i>, vol. 611, no. 7936, Springer Nature, 2022, pp. 614–22, doi:<a href=\"https://doi.org/10.1038/s41586-022-05386-6\">10.1038/s41586-022-05386-6</a>.","ama":"Buttress T, He S, Wang L, et al. Histone H2B.8 compacts flowering plant sperm through chromatin phase separation. <i>Nature</i>. 2022;611(7936):614-622. doi:<a href=\"https://doi.org/10.1038/s41586-022-05386-6\">10.1038/s41586-022-05386-6</a>","chicago":"Buttress, Toby, Shengbo He, Liang Wang, Shaoli Zhou, Gerhard Saalbach, Martin Vickers, Guohong Li, Pilong Li, and Xiaoqi Feng. “Histone H2B.8 Compacts Flowering Plant Sperm through Chromatin Phase Separation.” <i>Nature</i>. Springer Nature, 2022. <a href=\"https://doi.org/10.1038/s41586-022-05386-6\">https://doi.org/10.1038/s41586-022-05386-6</a>.","apa":"Buttress, T., He, S., Wang, L., Zhou, S., Saalbach, G., Vickers, M., … Feng, X. (2022). Histone H2B.8 compacts flowering plant sperm through chromatin phase separation. <i>Nature</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41586-022-05386-6\">https://doi.org/10.1038/s41586-022-05386-6</a>","ista":"Buttress T, He S, Wang L, Zhou S, Saalbach G, Vickers M, Li G, Li P, Feng X. 2022. Histone H2B.8 compacts flowering plant sperm through chromatin phase separation. Nature. 611(7936), 614–622.","short":"T. Buttress, S. He, L. Wang, S. Zhou, G. Saalbach, M. Vickers, G. Li, P. Li, X. Feng, Nature 611 (2022) 614–622.","ieee":"T. Buttress <i>et al.</i>, “Histone H2B.8 compacts flowering plant sperm through chromatin phase separation,” <i>Nature</i>, vol. 611, no. 7936. Springer Nature, pp. 614–622, 2022."},"intvolume":"       611","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1038/s41586-022-05386-6"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","abstract":[{"lang":"eng","text":"Sperm chromatin is typically transformed by protamines into a compact and transcriptionally inactive state1,2. Sperm cells of flowering plants lack protamines, yet they have small, transcriptionally active nuclei with chromatin condensed through an unknown mechanism3,4. Here we show that a histone variant, H2B.8, mediates sperm chromatin and nuclear condensation in Arabidopsis thaliana. Loss of H2B.8 causes enlarged sperm nuclei with dispersed chromatin, whereas ectopic expression in somatic cells produces smaller nuclei with aggregated chromatin. This result demonstrates that H2B.8 is sufficient for chromatin condensation. H2B.8 aggregates transcriptionally inactive AT-rich chromatin into phase-separated condensates, which facilitates nuclear compaction without reducing transcription. Reciprocal crosses show that mutation of h2b.8 reduces male transmission, which suggests that H2B.8-mediated sperm compaction is important for fertility. Altogether, our results reveal a new mechanism of nuclear compaction through global aggregation of unexpressed chromatin. We propose that H2B.8 is an evolutionary innovation of flowering plants that achieves nuclear condensation compatible with active transcription."}],"title":"Histone H2B.8 compacts flowering plant sperm through chromatin phase separation","_id":"12671","pmid":1},{"ec_funded":1,"status":"public","project":[{"_id":"0599E47C-7A3F-11EA-A408-12923DDC885E","grant_number":"863818","call_identifier":"H2020","name":"Formal Methods for Stochastic Models: Algorithms and Applications"}],"type":"preprint","date_published":"2022-09-28T00:00:00Z","main_file_link":[{"url":" https://doi.org/10.48550/arXiv.2209.14368","open_access":"1"}],"citation":{"ista":"Chatterjee K, Mohammadi M, Saona Urmeneta RJ. Repeated prophet inequality with near-optimal bounds. arXiv, 2209.14368.","apa":"Chatterjee, K., Mohammadi, M., &#38; Saona Urmeneta, R. J. (n.d.). Repeated prophet inequality with near-optimal bounds. <i>arXiv</i>. <a href=\"https://doi.org/10.48550/ARXIV.2209.14368\">https://doi.org/10.48550/ARXIV.2209.14368</a>","ieee":"K. Chatterjee, M. Mohammadi, and R. J. Saona Urmeneta, “Repeated prophet inequality with near-optimal bounds,” <i>arXiv</i>. .","short":"K. Chatterjee, M. Mohammadi, R.J. Saona Urmeneta, ArXiv (n.d.).","ama":"Chatterjee K, Mohammadi M, Saona Urmeneta RJ. Repeated prophet inequality with near-optimal bounds. <i>arXiv</i>. doi:<a href=\"https://doi.org/10.48550/ARXIV.2209.14368\">10.48550/ARXIV.2209.14368</a>","mla":"Chatterjee, Krishnendu, et al. “Repeated Prophet Inequality with Near-Optimal Bounds.” <i>ArXiv</i>, 2209.14368, doi:<a href=\"https://doi.org/10.48550/ARXIV.2209.14368\">10.48550/ARXIV.2209.14368</a>.","chicago":"Chatterjee, Krishnendu, Mona Mohammadi, and Raimundo J Saona Urmeneta. “Repeated Prophet Inequality with Near-Optimal Bounds.” <i>ArXiv</i>, n.d. <a href=\"https://doi.org/10.48550/ARXIV.2209.14368\">https://doi.org/10.48550/ARXIV.2209.14368</a>."},"external_id":{"arxiv":["2209.14368"]},"oa_version":"Preprint","_id":"12677","publication":"arXiv","doi":"10.48550/ARXIV.2209.14368","title":"Repeated prophet inequality with near-optimal bounds","date_updated":"2025-07-14T09:09:51Z","abstract":[{"lang":"eng","text":"In modern sample-driven Prophet Inequality, an adversary chooses a sequence of n items with values v1,v2,…,vn to be presented to a decision maker (DM). The process follows in two phases. In the first phase (sampling phase), some items, possibly selected at random, are revealed to the DM, but she can never accept them. In the second phase, the DM is presented with the other items in a random order and online fashion. For each item, she must make an irrevocable decision to either accept the item and stop the process or reject the item forever and proceed to the next item. The goal of the DM is to maximize the expected value as compared to a Prophet (or offline algorithm) that has access to all information. In this setting, the sampling phase has no cost and is not part of the optimization process. However, in many scenarios, the samples are obtained as part of the decision-making process.\r\nWe model this aspect as a two-phase Prophet Inequality where an adversary chooses a sequence of 2n items with values v1,v2,…,v2n and the items are randomly ordered. Finally, there are two phases of the Prophet Inequality problem with the first n-items and the rest of the items, respectively. We show that some basic algorithms achieve a ratio of at most 0.450. We present an algorithm that achieves a ratio of at least 0.495. Finally, we show that for every algorithm the ratio it can achieve is at most 0.502. Hence our algorithm is near-optimal."}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"No","acknowledgement":"This research was partially supported by the ERC CoG 863818 (ForM-SMArt) grant.","article_number":"2209.14368","oa":1,"month":"09","author":[{"first_name":"Krishnendu","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","full_name":"Chatterjee, Krishnendu","orcid":"0000-0002-4561-241X","last_name":"Chatterjee"},{"last_name":"Mohammadi","id":"4363614d-b686-11ed-a7d5-ac9e4a24bc2e","first_name":"Mona","full_name":"Mohammadi, Mona"},{"orcid":"0000-0001-5103-038X","last_name":"Saona Urmeneta","full_name":"Saona Urmeneta, Raimundo J","first_name":"Raimundo J","id":"BD1DF4C4-D767-11E9-B658-BC13E6697425"}],"publication_status":"submitted","day":"28","arxiv":1,"date_created":"2023-02-24T12:21:40Z","year":"2022","language":[{"iso":"eng"}],"department":[{"_id":"GradSch"},{"_id":"KrCh"}]},{"acknowledgement":"The authors warmly thank Amos Nevo for having presented the authors to each other during\r\na beautiful conference in Goa in February 2016, where the idea of this paper was born. The\r\nfirst author thanks the IHES for two post-doctoral years when most of this paper was discussed,\r\nand the Topology team in Orsay for financial support at the final stage. The first author was\r\nsupported by the EPRSC EP/P026710/1 grant. Finally, we warmly thank the referee for many\r\nvery helpful comments that have improved the readability of this paper.","_id":"12684","title":"Effective equidistribution of lattice points in positive characteristic","abstract":[{"text":"Given a place  ω  of a global function field  K  over a finite field, with associated affine function ring  Rω  and completion  Kω , the aim of this paper is to give an effective joint equidistribution result for renormalized primitive lattice points  (a,b)∈Rω2  in the plane  Kω2 , and for renormalized solutions to the gcd equation  ax+by=1 . The main tools are techniques of Goronik and Nevo for counting lattice points in well-rounded families of subsets. This gives a sharper analog in positive characteristic of a result of Nevo and the first author for the equidistribution of the primitive lattice points in  \\ZZ2 .","lang":"eng"}],"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","has_accepted_license":"1","citation":{"mla":"Horesh, Tal, and Frédéric Paulin. “Effective Equidistribution of Lattice Points in Positive Characteristic.” <i>Journal de Theorie Des Nombres de Bordeaux</i>, vol. 34, no. 3, Centre Mersenne, 2022, pp. 679–703, doi:<a href=\"https://doi.org/10.5802/JTNB.1222\">10.5802/JTNB.1222</a>.","ama":"Horesh T, Paulin F. Effective equidistribution of lattice points in positive characteristic. <i>Journal de Theorie des Nombres de Bordeaux</i>. 2022;34(3):679-703. doi:<a href=\"https://doi.org/10.5802/JTNB.1222\">10.5802/JTNB.1222</a>","chicago":"Horesh, Tal, and Frédéric Paulin. “Effective Equidistribution of Lattice Points in Positive Characteristic.” <i>Journal de Theorie Des Nombres de Bordeaux</i>. Centre Mersenne, 2022. <a href=\"https://doi.org/10.5802/JTNB.1222\">https://doi.org/10.5802/JTNB.1222</a>.","apa":"Horesh, T., &#38; Paulin, F. (2022). Effective equidistribution of lattice points in positive characteristic. <i>Journal de Theorie Des Nombres de Bordeaux</i>. Centre Mersenne. <a href=\"https://doi.org/10.5802/JTNB.1222\">https://doi.org/10.5802/JTNB.1222</a>","ista":"Horesh T, Paulin F. 2022. Effective equidistribution of lattice points in positive characteristic. Journal de Theorie des Nombres de Bordeaux. 34(3), 679–703.","short":"T. Horesh, F. Paulin, Journal de Theorie Des Nombres de Bordeaux 34 (2022) 679–703.","ieee":"T. Horesh and F. Paulin, “Effective equidistribution of lattice points in positive characteristic,” <i>Journal de Theorie des Nombres de Bordeaux</i>, vol. 34, no. 3. Centre Mersenne, pp. 679–703, 2022."},"intvolume":"        34","status":"public","file_date_updated":"2023-02-27T09:10:13Z","isi":1,"scopus_import":"1","publication_identifier":{"eissn":["2118-8572"],"issn":["1246-7405"]},"issue":"3","oa":1,"file":[{"relation":"main_file","creator":"dernst","file_id":"12689","date_created":"2023-02-27T09:10:13Z","content_type":"application/pdf","file_size":870468,"date_updated":"2023-02-27T09:10:13Z","checksum":"08f28fded270251f568f610cf5166d69","access_level":"open_access","file_name":"2023_JourTheorieNombreBordeaux_Horesh.pdf","success":1}],"quality_controlled":"1","month":"01","publication":"Journal de Theorie des Nombres de Bordeaux","date_updated":"2023-08-04T10:41:40Z","doi":"10.5802/JTNB.1222","publisher":"Centre Mersenne","article_processing_charge":"No","oa_version":"Published Version","article_type":"original","external_id":{"arxiv":["2001.01534"],"isi":["000926504300003"]},"volume":34,"type":"journal_article","date_published":"2022-01-27T00:00:00Z","tmp":{"image":"/image/cc_by_nd.png","legal_code_url":"https://creativecommons.org/licenses/by-nd/4.0/legalcode","name":"Creative Commons Attribution-NoDerivatives 4.0 International (CC BY-ND 4.0)","short":"CC BY-ND (4.0)"},"department":[{"_id":"TiBr"}],"year":"2022","language":[{"iso":"eng"}],"ddc":["510"],"publication_status":"published","day":"27","license":"https://creativecommons.org/licenses/by-nd/4.0/","arxiv":1,"date_created":"2023-02-26T23:01:02Z","page":"679-703","author":[{"last_name":"Horesh","full_name":"Horesh, Tal","id":"C8B7BF48-8D81-11E9-BCA9-F536E6697425","first_name":"Tal"},{"last_name":"Paulin","first_name":"Frédéric","full_name":"Paulin, Frédéric"}]},{"author":[{"last_name":"Brighi","orcid":"0000-0002-7969-2729","id":"4115AF5C-F248-11E8-B48F-1D18A9856A87","first_name":"Pietro","full_name":"Brighi, Pietro"},{"full_name":"Ljubotina, Marko","id":"F75EE9BE-5C90-11EA-905D-16643DDC885E","first_name":"Marko","orcid":"0000-0003-0038-7068","last_name":"Ljubotina"},{"orcid":"0000-0002-2399-5827","last_name":"Serbyn","first_name":"Maksym","id":"47809E7E-F248-11E8-B48F-1D18A9856A87","full_name":"Serbyn, Maksym"}],"date_created":"2023-03-23T14:33:13Z","arxiv":1,"publication_status":"submitted","day":"07","language":[{"iso":"eng"}],"year":"2022","related_material":{"record":[{"relation":"dissertation_contains","status":"public","id":"12732"},{"status":"public","relation":"later_version","id":"14334"}]},"department":[{"_id":"GradSch"},{"_id":"MaSe"}],"tmp":{"short":"CC BY-NC-SA (4.0)","name":"Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)","image":"/images/cc_by_nc_sa.png","legal_code_url":"https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode"},"date_published":"2022-11-07T00:00:00Z","type":"preprint","status":"public","oa_version":"Preprint","external_id":{"arxiv":["2210.15607"]},"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2210.15607"}],"citation":{"apa":"Brighi, P., Ljubotina, M., &#38; Serbyn, M. (n.d.). Hilbert space fragmentation and slow dynamics in particle-conserving quantum East models. <i>arXiv</i>. <a href=\"https://doi.org/10.48550/arXiv.2210.15607\">https://doi.org/10.48550/arXiv.2210.15607</a>","ista":"Brighi P, Ljubotina M, Serbyn M. Hilbert space fragmentation and slow dynamics in particle-conserving quantum East models. arXiv, 2210.15607.","ieee":"P. Brighi, M. Ljubotina, and M. Serbyn, “Hilbert space fragmentation and slow dynamics in particle-conserving quantum East models,” <i>arXiv</i>. .","short":"P. Brighi, M. Ljubotina, M. Serbyn, ArXiv (n.d.).","mla":"Brighi, Pietro, et al. “Hilbert Space Fragmentation and Slow Dynamics in Particle-Conserving Quantum East Models.” <i>ArXiv</i>, 2210.15607, doi:<a href=\"https://doi.org/10.48550/arXiv.2210.15607\">10.48550/arXiv.2210.15607</a>.","ama":"Brighi P, Ljubotina M, Serbyn M. Hilbert space fragmentation and slow dynamics in particle-conserving quantum East models. <i>arXiv</i>. doi:<a href=\"https://doi.org/10.48550/arXiv.2210.15607\">10.48550/arXiv.2210.15607</a>","chicago":"Brighi, Pietro, Marko Ljubotina, and Maksym Serbyn. “Hilbert Space Fragmentation and Slow Dynamics in Particle-Conserving Quantum East Models.” <i>ArXiv</i>, n.d. <a href=\"https://doi.org/10.48550/arXiv.2210.15607\">https://doi.org/10.48550/arXiv.2210.15607</a>."},"abstract":[{"lang":"eng","text":"Quantum kinetically constrained models have recently attracted significant attention due to their anomalous dynamics and thermalization. In this work, we introduce a hitherto unexplored family of kinetically constrained models featuring a conserved particle number and strong inversion-symmetry breaking due to facilitated hopping. We demonstrate that these models provide a generic example of so-called quantum Hilbert space fragmentation, that is manifested in disconnected sectors in the Hilbert space that are not apparent in the computational basis. Quantum Hilbert space fragmentation leads to an exponential in system size number of eigenstates with exactly zero entanglement entropy across several bipartite cuts. These eigenstates can be probed dynamically using quenches from simple initial product states. In addition, we study the particle spreading under unitary dynamics launched from the domain wall state, and find faster than diffusive dynamics at high particle densities, that crosses over into logarithmically slow relaxation at smaller densities. Using a classically simulable cellular automaton, we reproduce the logarithmic dynamics observed in the quantum case. Our work suggests that particle conserving constrained models with inversion symmetry breaking realize so far unexplored universality classes of dynamics and invite their further theoretical and experimental studies."}],"article_processing_charge":"No","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"12750","publication":"arXiv","date_updated":"2023-09-20T10:46:29Z","doi":"10.48550/arXiv.2210.15607","title":"Hilbert space fragmentation and slow dynamics in particle-conserving quantum East models","month":"11","article_number":"2210.15607","oa":1},{"publication_identifier":{"issn":["1868-8969"]},"file_date_updated":"2023-09-26T10:43:15Z","scopus_import":"1","has_accepted_license":"1","citation":{"short":"K. Grover, J. Kretinsky, T. Meggendorfer, M. Weininger, in:, 33rd International Conference on Concurrency Theory , Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022.","ieee":"K. Grover, J. Kretinsky, T. Meggendorfer, and M. Weininger, “Anytime guarantees for reachability in uncountable Markov decision processes,” in <i>33rd International Conference on Concurrency Theory </i>, Warsaw, Poland, 2022, vol. 243.","apa":"Grover, K., Kretinsky, J., Meggendorfer, T., &#38; Weininger, M. (2022). Anytime guarantees for reachability in uncountable Markov decision processes. In <i>33rd International Conference on Concurrency Theory </i> (Vol. 243). Warsaw, Poland: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. <a href=\"https://doi.org/10.4230/LIPIcs.CONCUR.2022.11\">https://doi.org/10.4230/LIPIcs.CONCUR.2022.11</a>","ista":"Grover K, Kretinsky J, Meggendorfer T, Weininger M. 2022. Anytime guarantees for reachability in uncountable Markov decision processes. 33rd International Conference on Concurrency Theory . CONCUR: Conference on Concurrency Theory, LIPIcs, vol. 243, 11.","chicago":"Grover, Kush, Jan Kretinsky, Tobias Meggendorfer, and Maimilian Weininger. “Anytime Guarantees for Reachability in Uncountable Markov Decision Processes.” In <i>33rd International Conference on Concurrency Theory </i>, Vol. 243. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. <a href=\"https://doi.org/10.4230/LIPIcs.CONCUR.2022.11\">https://doi.org/10.4230/LIPIcs.CONCUR.2022.11</a>.","mla":"Grover, Kush, et al. “Anytime Guarantees for Reachability in Uncountable Markov Decision Processes.” <i>33rd International Conference on Concurrency Theory </i>, vol. 243, 11, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022, doi:<a href=\"https://doi.org/10.4230/LIPIcs.CONCUR.2022.11\">10.4230/LIPIcs.CONCUR.2022.11</a>.","ama":"Grover K, Kretinsky J, Meggendorfer T, Weininger M. Anytime guarantees for reachability in uncountable Markov decision processes. In: <i>33rd International Conference on Concurrency Theory </i>. Vol 243. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2022. doi:<a href=\"https://doi.org/10.4230/LIPIcs.CONCUR.2022.11\">10.4230/LIPIcs.CONCUR.2022.11</a>"},"intvolume":"       243","status":"public","acknowledgement":"Kush Grover: The author has been supported by the DFG research training group GRK\r\n2428 ConVeY.\r\nMaximilian Weininger: The author has been partially supported by DFG projects 383882557\r\nStatistical Unbounded Verification (SUV) and 427755713 Group-By Objectives in Probabilistic\r\nVerification (GOPro)","abstract":[{"text":"We consider the problem of approximating the reachability probabilities in Markov decision processes (MDP) with uncountable (continuous) state and action spaces. While there are algorithms that, for special classes of such MDP, provide a sequence of approximations converging to the true value in the limit, our aim is to obtain an algorithm with guarantees on the precision of the approximation.\r\nAs this problem is undecidable in general, assumptions on the MDP are necessary. Our main contribution is to identify sufficient assumptions that are as weak as possible, thus approaching the \"boundary\" of which systems can be correctly and reliably analyzed. To this end, we also argue why each of our assumptions is necessary for algorithms based on processing finitely many observations.\r\nWe present two solution variants. The first one provides converging lower bounds under weaker assumptions than typical ones from previous works concerned with guarantees. The second one then utilizes stronger assumptions to additionally provide converging upper bounds. Altogether, we obtain an anytime algorithm, i.e. yielding a sequence of approximants with known and iteratively improving precision, converging to the true value in the limit. Besides, due to the generality of our assumptions, our algorithms are very general templates, readily allowing for various heuristics from literature in contrast to, e.g., a specific discretization algorithm. Our theoretical contribution thus paves the way for future practical improvements without sacrificing correctness guarantees.","lang":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"12775","title":"Anytime guarantees for reachability in uncountable Markov decision processes","arxiv":1,"date_created":"2023-03-28T08:09:32Z","publication_status":"published","day":"15","author":[{"full_name":"Grover, Kush","first_name":"Kush","last_name":"Grover"},{"orcid":"0000-0002-8122-2881","last_name":"Kretinsky","full_name":"Kretinsky, Jan","first_name":"Jan","id":"44CEF464-F248-11E8-B48F-1D18A9856A87"},{"orcid":"0000-0002-1712-2165","last_name":"Meggendorfer","full_name":"Meggendorfer, Tobias","first_name":"Tobias","id":"b21b0c15-30a2-11eb-80dc-f13ca25802e1"},{"full_name":"Weininger, Maimilian","first_name":"Maimilian","last_name":"Weininger"}],"alternative_title":["LIPIcs"],"conference":{"start_date":"2022-09-13","name":"CONCUR: Conference on Concurrency Theory","location":"Warsaw, Poland","end_date":"2022-09-16"},"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"department":[{"_id":"KrCh"}],"year":"2022","language":[{"iso":"eng"}],"ddc":["000"],"oa_version":"Published Version","external_id":{"arxiv":["2008.04824"]},"volume":243,"date_published":"2022-09-15T00:00:00Z","type":"conference","month":"09","article_number":"11","quality_controlled":"1","oa":1,"file":[{"relation":"main_file","creator":"dernst","file_id":"14372","date_created":"2023-09-26T10:43:15Z","content_type":"application/pdf","file_size":960036,"date_updated":"2023-09-26T10:43:15Z","checksum":"e282e43d3ae0ba6e067b72f4583e13c0","access_level":"open_access","file_name":"2022_LIPIcS_Grover.pdf","success":1}],"article_processing_charge":"No","publication":"33rd International Conference on Concurrency Theory ","publisher":"Schloss Dagstuhl - Leibniz-Zentrum für Informatik","doi":"10.4230/LIPIcs.CONCUR.2022.11","date_updated":"2023-09-26T10:43:30Z"},{"_id":"12776","title":"Revisiting the Manin–Peyre conjecture for the split del Pezzo surface of degree 5","abstract":[{"lang":"eng","text":"An improved asymptotic formula is established for the number of rational points of bounded height on the split smooth del Pezzo surface of degree 5. The proof uses the five conic bundle structures on the surface."}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","acknowledgement":"This work was begun while the author was participating in the programme on \"Diophantine equations\" at the Hausdorff Research Institute for Mathematics in Bonn in 2009. The hospitality and financial support of the institute is gratefully acknowledged. The idea of using conic bundles to study the split del Pezzo surface of degree 5 was explained to the author by Professor Salberger. The author is very grateful to him for his input into this project and also to Shuntaro Yamagishi for many useful comments on an earlier version of this manuscript. While working on this paper the author was supported by FWF grant P32428-N35.","status":"public","has_accepted_license":"1","intvolume":"        28","citation":{"ieee":"T. D. Browning, “Revisiting the Manin–Peyre conjecture for the split del Pezzo surface of degree 5,” <i>New York Journal of Mathematics</i>, vol. 28. State University of New York, pp. 1193–1229, 2022.","short":"T.D. Browning, New York Journal of Mathematics 28 (2022) 1193–1229.","apa":"Browning, T. D. (2022). Revisiting the Manin–Peyre conjecture for the split del Pezzo surface of degree 5. <i>New York Journal of Mathematics</i>. State University of New York.","ista":"Browning TD. 2022. Revisiting the Manin–Peyre conjecture for the split del Pezzo surface of degree 5. New York Journal of Mathematics. 28, 1193–1229.","chicago":"Browning, Timothy D. “Revisiting the Manin–Peyre Conjecture for the Split Del Pezzo Surface of Degree 5.” <i>New York Journal of Mathematics</i>. State University of New York, 2022.","mla":"Browning, Timothy D. “Revisiting the Manin–Peyre Conjecture for the Split Del Pezzo Surface of Degree 5.” <i>New York Journal of Mathematics</i>, vol. 28, State University of New York, 2022, pp. 1193–229.","ama":"Browning TD. Revisiting the Manin–Peyre conjecture for the split del Pezzo surface of degree 5. <i>New York Journal of Mathematics</i>. 2022;28:1193-1229."},"file_date_updated":"2023-03-30T07:09:35Z","publication_identifier":{"issn":["1076-9803"]},"publication":"New York Journal of Mathematics","date_updated":"2023-10-18T07:59:13Z","publisher":"State University of New York","article_processing_charge":"No","quality_controlled":"1","oa":1,"file":[{"file_size":897267,"date_updated":"2023-03-30T07:09:35Z","checksum":"c01e8291794a1bdb7416aa103cb68ef8","success":1,"access_level":"open_access","file_name":"2022_NYJM_Browning.pdf","creator":"dernst","relation":"main_file","date_created":"2023-03-30T07:09:35Z","file_id":"12778","content_type":"application/pdf"}],"month":"08","volume":28,"project":[{"grant_number":"P32428","_id":"26AEDAB2-B435-11E9-9278-68D0E5697425","name":"New frontiers of the Manin conjecture","call_identifier":"FWF"}],"type":"journal_article","date_published":"2022-08-24T00:00:00Z","oa_version":"Published Version","article_type":"original","language":[{"iso":"eng"}],"year":"2022","ddc":["510"],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"department":[{"_id":"TiBr"}],"page":"1193 - 1229","author":[{"full_name":"Browning, Timothy D","id":"35827D50-F248-11E8-B48F-1D18A9856A87","first_name":"Timothy D","orcid":"0000-0002-8314-0177","last_name":"Browning"}],"publication_status":"published","day":"24","date_created":"2023-03-28T09:21:09Z"},{"date_published":"2022-11-01T00:00:00Z","type":"conference","external_id":{"arxiv":["2111.08617"]},"oa_version":"Published Version","article_processing_charge":"Yes (via OA deal)","publication":"Proceedings of the 23rd ACM/IFIP International Middleware Conference","publisher":"Association for Computing Machinery","doi":"10.1145/3528535.3565248","date_updated":"2023-04-03T06:21:04Z","month":"11","quality_controlled":"1","file":[{"creator":"dernst","relation":"main_file","content_type":"application/pdf","file_id":"12795","date_created":"2023-04-03T06:17:58Z","date_updated":"2023-04-03T06:17:58Z","file_size":1514169,"access_level":"open_access","file_name":"2022_ACMMiddleware_Markov.pdf","success":1,"checksum":"1a397746235f245da5468819247ff663"}],"oa":1,"author":[{"last_name":"Markov","id":"D0CF4148-C985-11E9-8066-0BDEE5697425","first_name":"Ilia","full_name":"Markov, Ilia"},{"last_name":"Ramezanikebrya","full_name":"Ramezanikebrya, Hamidreza","first_name":"Hamidreza"},{"first_name":"Dan-Adrian","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","full_name":"Alistarh, Dan-Adrian","orcid":"0000-0003-3650-940X","last_name":"Alistarh"}],"page":"241-254","conference":{"start_date":"2022-11-07","name":"Middleware: International Middleware Conference","location":"Quebec, QC, Canada","end_date":"2022-11-11"},"date_created":"2023-03-31T06:17:00Z","arxiv":1,"publication_status":"published","day":"01","language":[{"iso":"eng"}],"year":"2022","ddc":["000"],"department":[{"_id":"DaAl"}],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"status":"public","has_accepted_license":"1","citation":{"chicago":"Markov, Ilia, Hamidreza Ramezanikebrya, and Dan-Adrian Alistarh. “CGX: Adaptive System Support for Communication-Efficient Deep Learning.” In <i>Proceedings of the 23rd ACM/IFIP International Middleware Conference</i>, 241–54. Association for Computing Machinery, 2022. <a href=\"https://doi.org/10.1145/3528535.3565248\">https://doi.org/10.1145/3528535.3565248</a>.","ama":"Markov I, Ramezanikebrya H, Alistarh D-A. CGX: Adaptive system support for communication-efficient deep learning. In: <i>Proceedings of the 23rd ACM/IFIP International Middleware Conference</i>. Association for Computing Machinery; 2022:241-254. doi:<a href=\"https://doi.org/10.1145/3528535.3565248\">10.1145/3528535.3565248</a>","mla":"Markov, Ilia, et al. “CGX: Adaptive System Support for Communication-Efficient Deep Learning.” <i>Proceedings of the 23rd ACM/IFIP International Middleware Conference</i>, Association for Computing Machinery, 2022, pp. 241–54, doi:<a href=\"https://doi.org/10.1145/3528535.3565248\">10.1145/3528535.3565248</a>.","short":"I. Markov, H. Ramezanikebrya, D.-A. Alistarh, in:, Proceedings of the 23rd ACM/IFIP International Middleware Conference, Association for Computing Machinery, 2022, pp. 241–254.","ieee":"I. Markov, H. Ramezanikebrya, and D.-A. Alistarh, “CGX: Adaptive system support for communication-efficient deep learning,” in <i>Proceedings of the 23rd ACM/IFIP International Middleware Conference</i>, Quebec, QC, Canada, 2022, pp. 241–254.","ista":"Markov I, Ramezanikebrya H, Alistarh D-A. 2022. CGX: Adaptive system support for communication-efficient deep learning. Proceedings of the 23rd ACM/IFIP International Middleware Conference. Middleware: International Middleware Conference, 241–254.","apa":"Markov, I., Ramezanikebrya, H., &#38; Alistarh, D.-A. (2022). CGX: Adaptive system support for communication-efficient deep learning. In <i>Proceedings of the 23rd ACM/IFIP International Middleware Conference</i> (pp. 241–254). Quebec, QC, Canada: Association for Computing Machinery. <a href=\"https://doi.org/10.1145/3528535.3565248\">https://doi.org/10.1145/3528535.3565248</a>"},"abstract":[{"text":"The ability to scale out training workloads has been one of the key performance enablers of deep learning. The main scaling approach is data-parallel GPU-based training, which has been boosted by hardware and software support for highly efficient point-to-point communication, and in particular via hardware bandwidth over-provisioning. Overprovisioning comes at a cost: there is an order of magnitude price difference between \"cloud-grade\" servers with such support, relative to their popular \"consumer-grade\" counterparts, although single server-grade and consumer-grade GPUs can have similar computational envelopes.\r\n\r\nIn this paper, we show that the costly hardware overprovisioning approach can be supplanted via algorithmic and system design, and propose a framework called CGX, which provides efficient software support for compressed communication in ML applications, for both multi-GPU single-node training, as well as larger-scale multi-node training. CGX is based on two technical advances: At the system level, it relies on a re-developed communication stack for ML frameworks, which provides flexible, highly-efficient support for compressed communication. At the application level, it provides seamless, parameter-free integration with popular frameworks, so that end-users do not have to modify training recipes, nor significant training code. This is complemented by a layer-wise adaptive compression technique which dynamically balances compression gains with accuracy preservation. CGX integrates with popular ML frameworks, providing up to 3X speedups for multi-GPU nodes based on commodity hardware, and order-of-magnitude improvements in the multi-node setting, with negligible impact on accuracy.","lang":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"12780","title":"CGX: Adaptive system support for communication-efficient deep learning","acknowledgement":"The authors sincerely thank Nikoli Dryden, Tal Ben-Nun, Torsten Hoefler and Bapi Chatterjee for useful discussions throughout the development of this project.","publication_identifier":{"isbn":["9781450393409"]},"file_date_updated":"2023-04-03T06:17:58Z"},{"day":"29","publication_status":"published","date_created":"2023-04-02T22:01:11Z","arxiv":1,"page":"193-237","keyword":["Arthur–Selberg trace formula","cuspidal automorphic representations","global function fields"],"author":[{"last_name":"Yu","orcid":"0000-0001-5128-7126","first_name":"Hongjie","id":"3D7DD9BE-F248-11E8-B48F-1D18A9856A87","full_name":"Yu, Hongjie"}],"department":[{"_id":"TaHa"}],"language":[{"iso":"eng"}],"year":"2022","article_type":"original","oa_version":"Preprint","external_id":{"isi":["000954466300006"],"arxiv":["2109.10245"]},"type":"journal_article","date_published":"2022-08-29T00:00:00Z","project":[{"call_identifier":"H2020","name":"ISTplus - Postdoctoral Fellowships","grant_number":"754411","_id":"260C2330-B435-11E9-9278-68D0E5697425"}],"volume":321,"quality_controlled":"1","oa":1,"month":"08","date_updated":"2023-08-04T10:42:38Z","publisher":"Mathematical Sciences Publishers","doi":"10.2140/pjm.2022.321.193","publication":"Pacific Journal of Mathematics","article_processing_charge":"No","publication_identifier":{"issn":["0030-8730"],"eissn":["1945-5844"]},"issue":"1","scopus_import":"1","isi":1,"intvolume":"       321","citation":{"mla":"Yu, Hongjie. “ A Coarse Geometric Expansion of a Variant of Arthur’s Truncated Traces and Some Applications.” <i>Pacific Journal of Mathematics</i>, vol. 321, no. 1, Mathematical Sciences Publishers, 2022, pp. 193–237, doi:<a href=\"https://doi.org/10.2140/pjm.2022.321.193\">10.2140/pjm.2022.321.193</a>.","ama":"Yu H.  A coarse geometric expansion of a variant of Arthur’s truncated traces and some applications. <i>Pacific Journal of Mathematics</i>. 2022;321(1):193-237. doi:<a href=\"https://doi.org/10.2140/pjm.2022.321.193\">10.2140/pjm.2022.321.193</a>","chicago":"Yu, Hongjie. “ A Coarse Geometric Expansion of a Variant of Arthur’s Truncated Traces and Some Applications.” <i>Pacific Journal of Mathematics</i>. Mathematical Sciences Publishers, 2022. <a href=\"https://doi.org/10.2140/pjm.2022.321.193\">https://doi.org/10.2140/pjm.2022.321.193</a>.","apa":"Yu, H. (2022).  A coarse geometric expansion of a variant of Arthur’s truncated traces and some applications. <i>Pacific Journal of Mathematics</i>. Mathematical Sciences Publishers. <a href=\"https://doi.org/10.2140/pjm.2022.321.193\">https://doi.org/10.2140/pjm.2022.321.193</a>","ista":"Yu H. 2022.  A coarse geometric expansion of a variant of Arthur’s truncated traces and some applications. Pacific Journal of Mathematics. 321(1), 193–237.","short":"H. Yu, Pacific Journal of Mathematics 321 (2022) 193–237.","ieee":"H. Yu, “ A coarse geometric expansion of a variant of Arthur’s truncated traces and some applications,” <i>Pacific Journal of Mathematics</i>, vol. 321, no. 1. Mathematical Sciences Publishers, pp. 193–237, 2022."},"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2109.10245"}],"status":"public","ec_funded":1,"acknowledgement":"I’d like to thank Prof. Chaudouard for introducing me to this area. I’d like to thank Prof. Harris for asking me the question that makes Section 10 possible. I’m grateful for the support of Prof. Hausel and IST Austria. The author was funded by an ISTplus fellowship: This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 754411.","title":" A coarse geometric expansion of a variant of Arthur's truncated traces and some applications","_id":"12793","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","abstract":[{"text":"Let F be a global function field with constant field Fq. Let G be a reductive group over Fq. We establish a variant of Arthur's truncated kernel for G and for its Lie algebra which generalizes Arthur's original construction. We establish a coarse geometric expansion for our variant truncation.\r\nAs applications, we consider some existence and uniqueness problems of some cuspidal automorphic representations for the functions field of the projective line P1Fq with two points of ramifications.","lang":"eng"}]},{"oa":1,"article_number":"2203.16701","month":"03","title":"Towards differential relational privacy and its use in question answering","doi":"10.48550/arXiv.2203.16701","date_updated":"2023-04-25T07:34:49Z","publication":"arXiv","_id":"12860","article_processing_charge":"No","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","abstract":[{"text":"Memorization of the relation between entities in a dataset can lead to privacy issues when using a trained model for question answering. We introduce Relational Memorization (RM) to understand, quantify and control this phenomenon. While bounding general memorization can have detrimental effects on the performance of a trained model, bounding RM does not prevent effective learning. The difference is most pronounced when the data distribution is long-tailed, with many queries having only few training examples: Impeding general memorization prevents effective learning, while impeding only relational memorization still allows learning general properties of the underlying concepts. We formalize the notion of Relational Privacy (RP) and, inspired by Differential Privacy (DP), we provide a possible definition of Differential Relational Privacy (DrP). These notions can be used to describe and compute bounds on the amount of RM in a trained model. We illustrate Relational Privacy concepts in experiments with large-scale models for Question Answering.","lang":"eng"}],"citation":{"mla":"Bombari, Simone, et al. “Towards Differential Relational Privacy and Its Use in Question Answering.” <i>ArXiv</i>, 2203.16701, doi:<a href=\"https://doi.org/10.48550/arXiv.2203.16701\">10.48550/arXiv.2203.16701</a>.","ama":"Bombari S, Achille A, Wang Z, et al. Towards differential relational privacy and its use in question answering. <i>arXiv</i>. doi:<a href=\"https://doi.org/10.48550/arXiv.2203.16701\">10.48550/arXiv.2203.16701</a>","chicago":"Bombari, Simone, Alessandro Achille, Zijian Wang, Yu-Xiang Wang, Yusheng Xie, Kunwar Yashraj Singh, Srikar Appalaraju, Vijay Mahadevan, and Stefano Soatto. “Towards Differential Relational Privacy and Its Use in Question Answering.” <i>ArXiv</i>, n.d. <a href=\"https://doi.org/10.48550/arXiv.2203.16701\">https://doi.org/10.48550/arXiv.2203.16701</a>.","apa":"Bombari, S., Achille, A., Wang, Z., Wang, Y.-X., Xie, Y., Singh, K. Y., … Soatto, S. (n.d.). Towards differential relational privacy and its use in question answering. <i>arXiv</i>. <a href=\"https://doi.org/10.48550/arXiv.2203.16701\">https://doi.org/10.48550/arXiv.2203.16701</a>","ista":"Bombari S, Achille A, Wang Z, Wang Y-X, Xie Y, Singh KY, Appalaraju S, Mahadevan V, Soatto S. Towards differential relational privacy and its use in question answering. arXiv, 2203.16701.","ieee":"S. Bombari <i>et al.</i>, “Towards differential relational privacy and its use in question answering,” <i>arXiv</i>. .","short":"S. Bombari, A. Achille, Z. Wang, Y.-X. Wang, Y. Xie, K.Y. Singh, S. Appalaraju, V. Mahadevan, S. Soatto, ArXiv (n.d.)."},"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2203.16701"}],"external_id":{"arxiv":["2203.16701"]},"oa_version":"Preprint","status":"public","date_published":"2022-03-30T00:00:00Z","type":"preprint","department":[{"_id":"GradSch"},{"_id":"MaMo"}],"year":"2022","language":[{"iso":"eng"}],"day":"30","publication_status":"submitted","arxiv":1,"date_created":"2023-04-23T16:11:48Z","author":[{"id":"ca726dda-de17-11ea-bc14-f9da834f63aa","first_name":"Simone","full_name":"Bombari, Simone","last_name":"Bombari"},{"last_name":"Achille","first_name":"Alessandro","full_name":"Achille, Alessandro"},{"last_name":"Wang","first_name":"Zijian","full_name":"Wang, Zijian"},{"last_name":"Wang","full_name":"Wang, Yu-Xiang","first_name":"Yu-Xiang"},{"first_name":"Yusheng","full_name":"Xie, Yusheng","last_name":"Xie"},{"first_name":"Kunwar Yashraj","full_name":"Singh, Kunwar Yashraj","last_name":"Singh"},{"last_name":"Appalaraju","first_name":"Srikar","full_name":"Appalaraju, Srikar"},{"first_name":"Vijay","full_name":"Mahadevan, Vijay","last_name":"Mahadevan"},{"full_name":"Soatto, Stefano","first_name":"Stefano","last_name":"Soatto"}]},{"abstract":[{"text":"Genetically informed, deep-phenotyped biobanks are an important research resource and it is imperative that the most powerful, versatile, and efficient analysis approaches are used. Here, we apply our recently developed Bayesian grouped mixture of regressions model (GMRM) in the UK and Estonian Biobanks and obtain the highest genomic prediction accuracy reported to date across 21 heritable traits. When compared to other approaches, GMRM accuracy was greater than annotation prediction models run in the LDAK or LDPred-funct software by 15% (SE 7%) and 14% (SE 2%), respectively, and was 18% (SE 3%) greater than a baseline BayesR model without single-nucleotide polymorphism (SNP) markers grouped into minor allele frequency–linkage disequilibrium (MAF-LD) annotation categories. For height, the prediction accuracy R 2 was 47% in a UK Biobank holdout sample, which was 76% of the estimated h SNP 2 . We then extend our GMRM prediction model to provide mixed-linear model association (MLMA) SNP marker estimates for genome-wide association (GWAS) discovery, which increased the independent loci detected to 16,162 in unrelated UK Biobank individuals, compared to 10,550 from BoltLMM and 10,095 from Regenie, a 62 and 65% increase, respectively. The average χ2 value of the leading markers increased by 15.24 (SE 0.41) for every 1% increase in prediction accuracy gained over a baseline BayesR model across the traits. Thus, we show that modeling genetic associations accounting for MAF and LD differences among SNP markers, and incorporating prior knowledge of genomic function, is important for both genomic prediction and discovery in large-scale individual-level studies.","lang":"eng"}],"article_processing_charge":"No","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"13064","date_updated":"2023-08-03T12:40:37Z","publisher":"Dryad","doi":"10.5061/DRYAD.GTHT76HMZ","title":"Improving genome-wide association discovery and genomic prediction accuracy in biobank data","month":"09","oa":1,"date_published":"2022-09-02T00:00:00Z","type":"research_data_reference","status":"public","oa_version":"Published Version","main_file_link":[{"open_access":"1","url":"https://doi.org/10.5061/dryad.gtht76hmz"}],"citation":{"apa":"Orliac, E., Trejo Banos, D., Ojavee, S., Läll, K., Mägi, R., Visscher, P., &#38; Robinson, M. R. (2022). Improving genome-wide association discovery and genomic prediction accuracy in biobank data. Dryad. <a href=\"https://doi.org/10.5061/DRYAD.GTHT76HMZ\">https://doi.org/10.5061/DRYAD.GTHT76HMZ</a>","ista":"Orliac E, Trejo Banos D, Ojavee S, Läll K, Mägi R, Visscher P, Robinson MR. 2022. Improving genome-wide association discovery and genomic prediction accuracy in biobank data, Dryad, <a href=\"https://doi.org/10.5061/DRYAD.GTHT76HMZ\">10.5061/DRYAD.GTHT76HMZ</a>.","short":"E. Orliac, D. Trejo Banos, S. Ojavee, K. Läll, R. Mägi, P. Visscher, M.R. Robinson, (2022).","ieee":"E. Orliac <i>et al.</i>, “Improving genome-wide association discovery and genomic prediction accuracy in biobank data.” Dryad, 2022.","mla":"Orliac, Etienne, et al. <i>Improving Genome-Wide Association Discovery and Genomic Prediction Accuracy in Biobank Data</i>. Dryad, 2022, doi:<a href=\"https://doi.org/10.5061/DRYAD.GTHT76HMZ\">10.5061/DRYAD.GTHT76HMZ</a>.","ama":"Orliac E, Trejo Banos D, Ojavee S, et al. Improving genome-wide association discovery and genomic prediction accuracy in biobank data. 2022. doi:<a href=\"https://doi.org/10.5061/DRYAD.GTHT76HMZ\">10.5061/DRYAD.GTHT76HMZ</a>","chicago":"Orliac, Etienne, Daniel Trejo Banos, Sven Ojavee, Kristi Läll, Reedik Mägi, Peter Visscher, and Matthew Richard Robinson. “Improving Genome-Wide Association Discovery and Genomic Prediction Accuracy in Biobank Data.” Dryad, 2022. <a href=\"https://doi.org/10.5061/DRYAD.GTHT76HMZ\">https://doi.org/10.5061/DRYAD.GTHT76HMZ</a>."},"ddc":["570"],"year":"2022","related_material":{"record":[{"status":"public","relation":"used_in_publication","id":"11733"}]},"department":[{"_id":"MaRo"}],"tmp":{"short":"CC0 (1.0)","name":"Creative Commons Public Domain Dedication (CC0 1.0)","image":"/images/cc_0.png","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode"},"author":[{"last_name":"Orliac","first_name":"Etienne","full_name":"Orliac, Etienne"},{"full_name":"Trejo Banos, Daniel","first_name":"Daniel","last_name":"Trejo Banos"},{"full_name":"Ojavee, Sven","first_name":"Sven","last_name":"Ojavee"},{"first_name":"Kristi","full_name":"Läll, Kristi","last_name":"Läll"},{"full_name":"Mägi, Reedik","first_name":"Reedik","last_name":"Mägi"},{"full_name":"Visscher, Peter","first_name":"Peter","last_name":"Visscher"},{"last_name":"Robinson","orcid":"0000-0001-8982-8813","first_name":"Matthew Richard","id":"E5D42276-F5DA-11E9-8E24-6303E6697425","full_name":"Robinson, Matthew Richard"}],"license":"https://creativecommons.org/publicdomain/zero/1.0/","date_created":"2023-05-23T16:28:13Z","day":"02"},{"date_published":"2022-07-28T00:00:00Z","type":"research_data_reference","status":"public","oa_version":"Published Version","citation":{"short":"E. Koch, M. Ravinet, A.M. Westram, K. Jonannesson, R. Butlin, (2022).","ieee":"E. Koch, M. Ravinet, A. M. Westram, K. Jonannesson, and R. Butlin, “Data from: Genetic architecture of repeated phenotypic divergence in Littorina saxatilis ecotype evolution.” Dryad, 2022.","apa":"Koch, E., Ravinet, M., Westram, A. M., Jonannesson, K., &#38; Butlin, R. (2022). Data from: Genetic architecture of repeated phenotypic divergence in Littorina saxatilis ecotype evolution. Dryad. <a href=\"https://doi.org/10.5061/DRYAD.M905QFV4B\">https://doi.org/10.5061/DRYAD.M905QFV4B</a>","ista":"Koch E, Ravinet M, Westram AM, Jonannesson K, Butlin R. 2022. Data from: Genetic architecture of repeated phenotypic divergence in Littorina saxatilis ecotype evolution, Dryad, <a href=\"https://doi.org/10.5061/DRYAD.M905QFV4B\">10.5061/DRYAD.M905QFV4B</a>.","chicago":"Koch, Eva, Mark Ravinet, Anja M Westram, Kerstin Jonannesson, and Roger Butlin. “Data from: Genetic Architecture of Repeated Phenotypic Divergence in Littorina Saxatilis Ecotype Evolution.” Dryad, 2022. <a href=\"https://doi.org/10.5061/DRYAD.M905QFV4B\">https://doi.org/10.5061/DRYAD.M905QFV4B</a>.","mla":"Koch, Eva, et al. <i>Data from: Genetic Architecture of Repeated Phenotypic Divergence in Littorina Saxatilis Ecotype Evolution</i>. Dryad, 2022, doi:<a href=\"https://doi.org/10.5061/DRYAD.M905QFV4B\">10.5061/DRYAD.M905QFV4B</a>.","ama":"Koch E, Ravinet M, Westram AM, Jonannesson K, Butlin R. Data from: Genetic architecture of repeated phenotypic divergence in Littorina saxatilis ecotype evolution. 2022. doi:<a href=\"https://doi.org/10.5061/DRYAD.M905QFV4B\">10.5061/DRYAD.M905QFV4B</a>"},"main_file_link":[{"url":"https://doi.org/10.5061/dryad.m905qfv4b","open_access":"1"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"No","abstract":[{"text":"Chromosomal inversions have been shown to play a major role in local adaptation by suppressing recombination between alternative arrangements and maintaining beneficial allele combinations. However, so far, their importance relative to the remaining genome remains largely unknown. Understanding the genetic architecture of adaptation requires better estimates of how loci of different effect sizes contribute to phenotypic variation. Here, we used three Swedish islands where the marine snail Littorina saxatilis has repeatedly evolved into two distinct ecotypes along a habitat transition. We estimated the contribution of inversion polymorphisms to phenotypic divergence while controlling for polygenic effects in the remaining genome using a quantitative genetics framework. We confirmed the importance of inversions but showed that contributions of loci outside inversions are of similar magnitude, with variable proportions dependent on the trait and the population. Some inversions showed consistent effects across all sites, whereas others exhibited site-specific effects, indicating that the genomic basis for replicated phenotypic divergence is only partly shared. The contributions of sexual dimorphism as well as environmental factors to phenotypic variation were significant but minor compared to inversions and polygenic background. Overall, this integrated approach provides insight into the multiple mechanisms contributing to parallel phenotypic divergence.","lang":"eng"}],"doi":"10.5061/DRYAD.M905QFV4B","publisher":"Dryad","date_updated":"2023-08-04T09:42:10Z","title":"Data from: Genetic architecture of repeated phenotypic divergence in Littorina saxatilis ecotype evolution","_id":"13066","month":"07","oa":1,"author":[{"full_name":"Koch, Eva","first_name":"Eva","last_name":"Koch"},{"first_name":"Mark","full_name":"Ravinet, Mark","last_name":"Ravinet"},{"first_name":"Anja M","id":"3C147470-F248-11E8-B48F-1D18A9856A87","full_name":"Westram, Anja M","orcid":"0000-0003-1050-4969","last_name":"Westram"},{"last_name":"Jonannesson","first_name":"Kerstin","full_name":"Jonannesson, Kerstin"},{"last_name":"Butlin","full_name":"Butlin, Roger","first_name":"Roger"}],"date_created":"2023-05-23T16:33:12Z","day":"28","related_material":{"record":[{"relation":"used_in_publication","status":"public","id":"12247"}]},"year":"2022","ddc":["570"],"department":[{"_id":"NiBa"}],"tmp":{"short":"CC0 (1.0)","name":"Creative Commons Public Domain Dedication (CC0 1.0)","image":"/images/cc_0.png","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode"}},{"year":"2022","ddc":["510"],"related_material":{"record":[{"id":"11180","relation":"used_in_publication","status":"public"}],"link":[{"relation":"software","url":"https://github.com/npostnikova/mq-based-schedulers/tree/v1.1"}]},"department":[{"_id":"DaAl"}],"author":[{"last_name":"Postnikova","first_name":"Anastasiia","full_name":"Postnikova, Anastasiia"},{"first_name":"Nikita","id":"2F4DB10C-F248-11E8-B48F-1D18A9856A87","full_name":"Koval, Nikita","last_name":"Koval"},{"first_name":"Giorgi","id":"3279A00C-F248-11E8-B48F-1D18A9856A87","full_name":"Nadiradze, Giorgi","last_name":"Nadiradze"},{"orcid":"0000-0003-3650-940X","last_name":"Alistarh","first_name":"Dan-Adrian","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","full_name":"Alistarh, Dan-Adrian"}],"day":"03","date_created":"2023-05-23T17:05:40Z","_id":"13076","doi":"10.5281/ZENODO.5733408","publisher":"Zenodo","date_updated":"2023-08-03T06:48:34Z","title":"Multi-queues can be state-of-the-art priority schedulers","abstract":[{"text":"The source code for replicating experiments presented in the paper.\r\n\r\nThe implementation of the designed priority schedulers can be found in Galois-2.2.1/include/Galois/WorkList/:\r\nStealingMultiQueue.h is the StealingMultiQueue.\r\nMQOptimized/ contains MQ Optimized variants.\r\n\r\nWe provide images that contain all the dependencies and datasets. Images can be pulled from npostnikova/mq-based-schedulers repository, or downloaded from Zenodo. See readme for more detail.","lang":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"No","oa":1,"month":"01","status":"public","type":"research_data_reference","date_published":"2022-01-03T00:00:00Z","main_file_link":[{"open_access":"1","url":"https://doi.org/10.5281/zenodo.5813846"}],"citation":{"chicago":"Postnikova, Anastasiia, Nikita Koval, Giorgi Nadiradze, and Dan-Adrian Alistarh. “Multi-Queues Can Be State-of-the-Art Priority Schedulers.” Zenodo, 2022. <a href=\"https://doi.org/10.5281/ZENODO.5733408\">https://doi.org/10.5281/ZENODO.5733408</a>.","mla":"Postnikova, Anastasiia, et al. <i>Multi-Queues Can Be State-of-the-Art Priority Schedulers</i>. Zenodo, 2022, doi:<a href=\"https://doi.org/10.5281/ZENODO.5733408\">10.5281/ZENODO.5733408</a>.","ama":"Postnikova A, Koval N, Nadiradze G, Alistarh D-A. Multi-queues can be state-of-the-art priority schedulers. 2022. doi:<a href=\"https://doi.org/10.5281/ZENODO.5733408\">10.5281/ZENODO.5733408</a>","short":"A. Postnikova, N. Koval, G. Nadiradze, D.-A. Alistarh, (2022).","ieee":"A. Postnikova, N. Koval, G. Nadiradze, and D.-A. Alistarh, “Multi-queues can be state-of-the-art priority schedulers.” Zenodo, 2022.","apa":"Postnikova, A., Koval, N., Nadiradze, G., &#38; Alistarh, D.-A. (2022). Multi-queues can be state-of-the-art priority schedulers. Zenodo. <a href=\"https://doi.org/10.5281/ZENODO.5733408\">https://doi.org/10.5281/ZENODO.5733408</a>","ista":"Postnikova A, Koval N, Nadiradze G, Alistarh D-A. 2022. Multi-queues can be state-of-the-art priority schedulers, Zenodo, <a href=\"https://doi.org/10.5281/ZENODO.5733408\">10.5281/ZENODO.5733408</a>."},"oa_version":"Published Version"},{"department":[{"_id":"TiVo"}],"language":[{"iso":"eng"}],"year":"2022","ddc":["000"],"date_created":"2023-07-16T22:01:12Z","publication_status":"published","day":"01","author":[{"last_name":"Van Der Plas","full_name":"Van Der Plas, Thijs L.","first_name":"Thijs L."},{"last_name":"Vogels","orcid":"0000-0003-3295-6181","full_name":"Vogels, Tim P","first_name":"Tim P","id":"CB6FF8D2-008F-11EA-8E08-2637E6697425"},{"full_name":"Manohar, Sanjay G.","first_name":"Sanjay G.","last_name":"Manohar"}],"page":"518-531","month":"12","file":[{"checksum":"7530a93ef42e10b4db1e5e4b69796e93","success":1,"access_level":"open_access","file_name":"2022_PMLR_vanderPlas.pdf","file_size":585135,"date_updated":"2023-07-18T06:32:38Z","date_created":"2023-07-18T06:32:38Z","file_id":"13243","content_type":"application/pdf","relation":"main_file","creator":"dernst"}],"quality_controlled":"1","oa":1,"article_processing_charge":"No","publication":"Proceedings of Machine Learning Research","publisher":"ML Research Press","date_updated":"2023-07-18T06:36:28Z","oa_version":"Published Version","volume":199,"project":[{"grant_number":"819603","_id":"0aacfa84-070f-11eb-9043-d7eb2c709234","name":"Learning the shape of synaptic plasticity rules for neuronal architectures and function through machine learning.","call_identifier":"H2020"}],"date_published":"2022-12-01T00:00:00Z","type":"conference","file_date_updated":"2023-07-18T06:32:38Z","scopus_import":"1","publication_identifier":{"eissn":["2640-3498"]},"acknowledgement":"The authors would like to thank members of the Vogels lab and Manohar lab, as well as Adam Packer, Andrew Saxe, Stefano Sarao Mannelli and Jacob Bakermans for fruitful discussions and comments on earlier versions of the manuscript.\r\nTLvdP was supported by funding from the Biotechnology and Biological Sciences Research Council (BBSRC) [grant number BB/M011224/1]. TPV was supported by an ERC Consolidator Grant (SYNAPSEEK). SGM was funded by a MRC Clinician Scientist Fellowship MR/P00878X and Leverhulme Grant RPG-2018-310.","abstract":[{"lang":"eng","text":"Brains are thought to engage in predictive learning - learning to predict upcoming stimuli - to construct an internal model of their environment. This is especially notable for spatial navigation, as first described by Tolman’s latent learning tasks. However, predictive learning has also been observed in sensory cortex, in settings unrelated to spatial navigation. Apart from normative frameworks such as active inference or efficient coding, what could be the utility of learning to predict the patterns of occurrence of correlated stimuli? Here we show that prediction, and thereby the construction of an internal model of sequential stimuli, can bootstrap the learning process of a working memory task in a recurrent neural network. We implemented predictive learning alongside working memory match-tasks, and networks emerged to solve the prediction task first by encoding information across time to predict upcoming stimuli, and then eavesdropped on this solution to solve the matching task. Eavesdropping was most beneficial when neural resources were limited. Hence, predictive learning acts as a general neural mechanism to learn to store sensory information that can later be essential for working memory tasks."}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"13239","title":"Predictive learning enables neural networks to learn complex working memory tasks","has_accepted_license":"1","intvolume":"       199","citation":{"mla":"Van Der Plas, Thijs L., et al. “Predictive Learning Enables Neural Networks to Learn Complex Working Memory Tasks.” <i>Proceedings of Machine Learning Research</i>, vol. 199, ML Research Press, 2022, pp. 518–31.","ama":"Van Der Plas TL, Vogels TP, Manohar SG. Predictive learning enables neural networks to learn complex working memory tasks. In: <i>Proceedings of Machine Learning Research</i>. Vol 199. ML Research Press; 2022:518-531.","chicago":"Van Der Plas, Thijs L., Tim P Vogels, and Sanjay G. Manohar. “Predictive Learning Enables Neural Networks to Learn Complex Working Memory Tasks.” In <i>Proceedings of Machine Learning Research</i>, 199:518–31. ML Research Press, 2022.","apa":"Van Der Plas, T. L., Vogels, T. P., &#38; Manohar, S. G. (2022). Predictive learning enables neural networks to learn complex working memory tasks. In <i>Proceedings of Machine Learning Research</i> (Vol. 199, pp. 518–531). ML Research Press.","ista":"Van Der Plas TL, Vogels TP, Manohar SG. 2022. Predictive learning enables neural networks to learn complex working memory tasks. Proceedings of Machine Learning Research. vol. 199, 518–531.","ieee":"T. L. Van Der Plas, T. P. Vogels, and S. G. Manohar, “Predictive learning enables neural networks to learn complex working memory tasks,” in <i>Proceedings of Machine Learning Research</i>, 2022, vol. 199, pp. 518–531.","short":"T.L. Van Der Plas, T.P. Vogels, S.G. Manohar, in:, Proceedings of Machine Learning Research, ML Research Press, 2022, pp. 518–531."},"ec_funded":1,"status":"public"},{"author":[{"full_name":"Ingole, Kishor D.","first_name":"Kishor D.","last_name":"Ingole"},{"full_name":"Nagarajan, Nithya","first_name":"Nithya","last_name":"Nagarajan"},{"first_name":"Simon","full_name":"Uhse, Simon","last_name":"Uhse"},{"first_name":"Caterina","id":"e3fdddd5-f6e0-11ea-865d-ca99ee6367f4","full_name":"Giannini, Caterina","last_name":"Giannini"},{"last_name":"Djamei","first_name":"Armin","full_name":"Djamei, Armin"}],"date_created":"2023-07-16T22:01:12Z","publication_status":"published","day":"19","language":[{"iso":"eng"}],"ddc":["579"],"year":"2022","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"department":[{"_id":"JiFr"}],"volume":3,"type":"journal_article","date_published":"2022-10-19T00:00:00Z","oa_version":"Published Version","article_type":"original","article_processing_charge":"Yes","publication":"Frontiers in Fungal Biology","doi":"10.3389/ffunb.2022.1029114","date_updated":"2024-03-06T14:01:57Z","publisher":"Frontiers Media","month":"10","article_number":"1029114","file":[{"file_size":27966699,"date_updated":"2023-07-17T11:46:34Z","checksum":"2254e0119c0749d6f7237084fefcece6","file_name":"2023_FrontiersFungalBio_Ingole.pdf","access_level":"open_access","success":1,"creator":"dernst","relation":"main_file","file_id":"13242","date_created":"2023-07-17T11:46:34Z","content_type":"application/pdf"}],"quality_controlled":"1","oa":1,"publication_identifier":{"eissn":["2673-6128"]},"scopus_import":"1","file_date_updated":"2023-07-17T11:46:34Z","status":"public","has_accepted_license":"1","intvolume":"         3","citation":{"apa":"Ingole, K. D., Nagarajan, N., Uhse, S., Giannini, C., &#38; Djamei, A. (2022). Tetracycline-controlled (TetON) gene expression system for the smut fungus Ustilago maydis. <i>Frontiers in Fungal Biology</i>. Frontiers Media. <a href=\"https://doi.org/10.3389/ffunb.2022.1029114\">https://doi.org/10.3389/ffunb.2022.1029114</a>","ista":"Ingole KD, Nagarajan N, Uhse S, Giannini C, Djamei A. 2022. Tetracycline-controlled (TetON) gene expression system for the smut fungus Ustilago maydis. Frontiers in Fungal Biology. 3, 1029114.","short":"K.D. Ingole, N. Nagarajan, S. Uhse, C. Giannini, A. Djamei, Frontiers in Fungal Biology 3 (2022).","ieee":"K. D. Ingole, N. Nagarajan, S. Uhse, C. Giannini, and A. Djamei, “Tetracycline-controlled (TetON) gene expression system for the smut fungus Ustilago maydis,” <i>Frontiers in Fungal Biology</i>, vol. 3. Frontiers Media, 2022.","mla":"Ingole, Kishor D., et al. “Tetracycline-Controlled (TetON) Gene Expression System for the Smut Fungus Ustilago Maydis.” <i>Frontiers in Fungal Biology</i>, vol. 3, 1029114, Frontiers Media, 2022, doi:<a href=\"https://doi.org/10.3389/ffunb.2022.1029114\">10.3389/ffunb.2022.1029114</a>.","ama":"Ingole KD, Nagarajan N, Uhse S, Giannini C, Djamei A. Tetracycline-controlled (TetON) gene expression system for the smut fungus Ustilago maydis. <i>Frontiers in Fungal Biology</i>. 2022;3. doi:<a href=\"https://doi.org/10.3389/ffunb.2022.1029114\">10.3389/ffunb.2022.1029114</a>","chicago":"Ingole, Kishor D., Nithya Nagarajan, Simon Uhse, Caterina Giannini, and Armin Djamei. “Tetracycline-Controlled (TetON) Gene Expression System for the Smut Fungus Ustilago Maydis.” <i>Frontiers in Fungal Biology</i>. Frontiers Media, 2022. <a href=\"https://doi.org/10.3389/ffunb.2022.1029114\">https://doi.org/10.3389/ffunb.2022.1029114</a>."},"abstract":[{"text":"Ustilago maydis is a biotrophic phytopathogenic fungus that causes corn smut disease. As a well-established model system, U. maydis is genetically fully accessible with large omics datasets available and subject to various biological questions ranging from DNA-repair, RNA-transport, and protein secretion to disease biology. For many genetic approaches, tight control of transgene regulation is important. Here we established an optimised version of the Tetracycline-ON (TetON) system for U. maydis. We demonstrate the Tetracycline concentration-dependent expression of fluorescent protein transgenes and the system’s suitability for the induced expression of the toxic protein BCL2 Associated X-1 (Bax1). The Golden Gate compatible vector system contains a native minimal promoter from the mating factor a-1 encoding gene, mfa with ten copies of the tet-regulated operator (tetO) and a codon optimised Tet-repressor (tetR*) which is translationally fused to the native transcriptional corepressor Mql1 (UMAG_05501). The metabolism-independent transcriptional regulator system is functional both, in liquid culture as well as on solid media in the presence of the inducer and can become a useful tool for toxin-antitoxin studies, identification of antifungal proteins, and to study functions of toxic gene products in Ustilago maydis.","lang":"eng"}],"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","_id":"13240","title":"Tetracycline-controlled (TetON) gene expression system for the smut fungus Ustilago maydis","acknowledgement":"The research leading to these results received funding from the European Research Council under the European Union’s Seventh Framework Programme ERC-2013-STG (grant agreement: 335691), the Austrian Science Fund (I 3033-B22), the Austrian Academy of Sciences, and the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy EXC-2070-390732324 (PhenoRob) and DFG grant (DJ 64/5-1).\r\nWe would like to thank the GMI/IMBA/IMP core facilities for their excellent technical support. We would like to acknowledge Dr. Sinéad A. O’Sullivan from DZNE, University of Bonn for providing anti-GFP antibodies. The authors are thankful to the Excellence University of Bonn for providing infrastructure and instrumentation facilities at the INRES-Plant Pathology department."}]