Sivan Sabato

Department of Computer Science, Ben Gurion University of the Negev

sabatos@cs.bgu.ac.il

Edited Volumes

V. Feldman (ed.), K. Ligett (ed.), S. Sabato (ed.), "Algorithmic Learning Theory, 16-19 March 2021, Virtual Conference, Worldwide", Proceedings of Machine Learning Research (PMLR) Volume 132:1-1285, 2021. [link to proceedings]

Journal Papers

N. Ben-David, S. Sabato, "Active Structure Learning of Bayesian Networks in an Observational Setting", Journal of Machine Learning Research, to appear. [preprint][code]

S. Hanneke, A. Kontorovich, S. Sabato, R. Weiss, "Universal Bayes consistency in metric spaces", Annals of Statistics, 49 (4) 2129--2150, August 2021. [link to publication][free version]

G. Keren, S. Sabato, B. Schuller, "Analysis of Loss Functions for Fast Single-Class Classification", Knowledge and Information Systems 62, 337-358, 2020. [link to publication]

E. Barash, N. Sal-Man, S. Sabato, M. Ziv-Ukelson, "BacPaCS-Bacterial Pathogenicity Classification via Sparse-SVM", Bioinformatics, 35(12):2001-2008, 2018. [link to publication][accepted manuscript (free access)][code]

S. Sabato, T. Hess, "Interactive Algorithms: Pool, Stream and Precognitive Stream", Journal of Machine Learning Research, 18(229):1--39, 2018. [link to publication]

A. Kontorovich, S. Sabato, R. Urner, "Active Nearest-Neighbor Learning in Metric Spaces", Journal of Machine Learning Research, 18(195):1--38, 2018. [link to publication]

S. Sabato, "Submodular Learning and Covering with Response-Dependent Costs ", Theoretical Computer Science, 742:98--113, 2018. [official publication][free version]

D. Hsu and S. Sabato, "Loss minimization and parameter estimation with heavy tails", Journal of Machine Learning Research, 17(18):1-40, 2016. [link to publication]

A. Daniely, S. Sabato, S. Ben-David, and S. Shalev-Shwartz, "Multiclass learnability and the ERM principle", Journal of Machine Learning Research, 16(Dec):2377−2404, 2015. [link to publication]

S. Sabato, S. Shalev-Shwartz, N. Srebro, D. Hsu, and T. Zhang, "Learning Sparse Low-Threshold Linear Classifiers", Journal of Machine Learning Research, 16(Jul):1275-1304, 2015 [link to publication]

A. Gonen, S. Sabato and S. Shalev-Shwartz, "Efficient Active Learning of Halfspaces: an Aggressive Approach", Journal of Machine Learning Research, 14(Sep):2487-2519, 2013 [link to publication]

S. Sabato, N. Srebro and N. Tishby, "Distribution-Dependent Sample Complexity of Large Margin Learning", Journal of Machine Learning Research, 14(Jul):2119-2149, 2013. [link to publication]

D. Aran, S. Sabato and A. Hellman, "DNA methylation of distal regulatory sites characterizes dysregulation of cancer genes", Genome Biology, 2013 14:R21 [link to publication]

S. Sabato and N. Tishby, "Multi-Instance Learning with Any Hypothesis Class", Journal of Machine Learning Research, 13(Oct):2999-3039, 2012.[link to publication]

S. Sabato and Y. Winter, "Relational Domains and the Interpretation of Reciprocals", Linguistics and Philosophy (2012) 35:191-241. [pdf] [bibtex]

O.Shamir, S. Sabato and N. Tishby, "Learning and Generalization with the Information Bottleneck", Theoretical Computer Science, Volume 411, Issues 29-30, Pages 2696-2711, June 2010. [official publication][pdf]

S. Sabato and S. Shalev-Shwartz, "Ranking Categorical Features Using Generalization Properties", Journal of Machine Learning Research, 9(Jun):1083-1114, 2008. [link to publication]

Conference Papers

N. Ben-David, S. Sabato, "A Fast Algorithm for PAC Combinatorial Pure Exploration; Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2022, to appear. [preprint][code]

T. Hess, M. Moshkovitz, S. Sabato, "A Constant Approximation Algorithm for Sequential Random-Order No-Substitution k-Median Clustering", Neural Information Processing Systems (NeurIPS), 3298--3308, 2021. [link to publication]

N. Barak, S. Sabato, "Approximating a Distribution Using Weight Queries", Proceedings of the 38th International Conference on Machine Learning (ICML), PMLR 139:674-683, 2021. [link to publication][code]

S. Schnapp, S. Sabato, "Active Feature Selection for the Mutual Information Criterion", Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 35(11), 9497-9504, 2021. [link to publication][code]

S. Sabato, E. Yom-Tov, "Bounding the Fairness and Accuracy of Classifiers from Population Statistics", The 37th International Conference on Machine Learning (ICML), Proceedings of Machine Learning Research 119:8316-8325, 2020. [link to publication][code]

T. Hess, S. Sabato, "Sequential no-Substitution k-Median-Clustering", Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics (AISTATS), 962--972, 2020. [link to publication][code]

S. Dasgupta, S. Sabato, "Robust Learning from Discriminative Feature Feedback", Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics (AISTATS), 973--982, 2020. [link to publication]

S. Sabato, "Epsilon-Best-Arm Identification in Pay-Per-Reward Multi-Armed Bandits", Neural Information Processing Systems (NeurIPS), 2880--2890, 2019. [link to publication]

G. Keren, S. Sabato, B. Schuller, "A Walkthrough for the Principle of Logit Separation", International Joint Conference on Artificial Intelligence (IJCAI), Best Paper from Sister Conference Track, 6191--6195, 2019. [link to publication]

E. Gutflaish, A. Kontorovich, S. Sabato, O. Biller, O. Sofer, "Temporal anomaly detection: calibrating the surprise" Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 3755-3762, 2019. [link to publication][code]

S. Dasgupta, A. Dey, N. Roberts, S. Sabato, "Learning from discriminative feature feedback", Advances in Neural Information Processing Systems 31 (NeurIPS), 3959--3967, 2018. [link to publication]

G. Keren, S. Sabato, B. Schuller, "Fast Single-Class Classification and the Principle of Logit Separation", International Conference on Data Mining (ICDM), 227--236, 2018. Best Student Paper Award [link to publication][arxiv version (free access)]

A. Kontorovich, S. Sabato, R. Weiss, "Nearest-Neighbor Sample Compression: Efficiency, Consistency, Infinite Dimensions", Advances in Neural Information Processing Systems 30 (NIPS), 1573--1583, 2017.[link to publication][extended version, with correction (see remark 1)]

G. Keren, S. Sabato, B. Schuller, "Tunable Sensitivity to Large Errors in Neural Network Training", 31st AAAI Conference on Artificial Intelligence, 2017. [link to publication] [bibtex]

A. Kontorovich, S. Sabato, R. Urner, "Active Nearest-Neighbor Learning in Metric Spaces", Advances in Neural Information Processing Systems 29 (NIPS), 856-864, 2016. [link to publication] [extended version]

S. Sabato, "Submodular Learning and Covering with Response-Dependent Costs" 27th International conference on Algorithmic Learning Theory (ALT), 130-144, 2016. [pdf]

S. Sabato and T. Hess, "Interactive Algorithms: from Pool to Stream", Proceedings of the 29th Annual Conference on Learning Theory (COLT), JMLR Workshop and Conference Proceedings 49:1419-1439, 2016. [link to publication]

S. Sabato and R. Munos, "Active Regression by Stratification", Advances in Neural Information Processing Systems (NIPS) 469-477, 2014. [link to publication][extended version]

D. Hsu and S. Sabato, "Heavy-tailed Regression with a Generalized Median-of-means", Proceedings of the 31st International Conference on Machine Learning (ICML), JMLR Workshop and Conference Proceedings 32(1):37-45, 2014. [pdf][extended version][bibtex][code]

S. Sabato, A. Sarwate, N. Srebro, "Auditing: Active Learning with Outcome-Dependent Query Costs", Neural Information Processing Systems 26 (NIPS), 512-520, 2013. [pdf][extended version] [bibtex]

A. Gonen, S. Sabato and S. Shalev-Shwartz, "Efficient Active Learning of Halfspaces: an Aggressive Approach", Prooceedings of the 30th International Conference on Machine Learning (ICML), JMLR Workshop and Conference Proceedings 28(1):480-488, 2013. [pdf][extended version][bibtex]

S. Sabato and A. Kalai, "Feature Multi-Selection among Subjective Features", Proceedings of the 30th International Conference on Machine Learning (ICML), JMLR Workshop and Conference Proceedings 28(3):810-818, 2013. Presented also at MLCrowd workshop at ICML 2013. [pdf][extended version][bibtex][code]

R. Ackerman, S. Ben-David, D. Locker, S. Sabato, "Clustering Oligarchies", Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS), JMLR Workshop and Conference Proceedings 31:66-74, 2013. [pdf][bibtex]

A. Daniely, S. Sabato and S. Shalev-Shwartz, "Multiclass Learning Approaches: A Theoretical Comparison with Implications", Neural Information Processing Systems 25 (NIPS), 2012, Pages 485-493. [pdf][bibtex]

A. Daniely, S. Sabato, S. Ben-David, S. Shalev-Shwartz, "Multiclass Learnability and the ERM principle", 24nd Annual Conference on Learning Theory (COLT) 2011, Best Student Paper Award. [pdf][extended version][bibtex]

S. Sabato, N. Srebro and N. Tishby, "Tight Sample Complexity of Large-Margin Learning", Neural Information Processing Systems 23 (NIPS), 2010. [extended version, with corrections][bibtex]

S. Sabato, N. Srebro and N. Tishby, "Reducing Label Complexity by Learning from Bags", Proceedings of the 13th International Conference on Artificial Intelligence and Statistics (AISTATS), 2010 [extended version][bibtex]

S. Sabato, N. Tishby, "Homogeneous Multi-Instance Learning with Arbitrary Dependence", Proceedings of The Twenty Second Annual Conference on Learning Theory (COLT), 2009. [pdf][bibtex]

O. Shamir, S. Sabato, and N. Tishby, "Learning and Generalization with the Information Bottleneck", Proceedings of Algorithmic Learning Theory (ALT) 2008. [pdf] [extended version][bibtex]

S. Sabato, S. Shalev-Shwartz, "Prediction by categorical features: generalization properties and application to feature ranking", Proceedings of The Twentieth Annual Conference on Learning Theory (COLT), 2007. [pdf] [extended version][bibtex]

S. Sabato, E. Yom-Tov, and O. Rodeh, "Melody - Expert-Free System Analysis", Machine Learning for Systems Problems Workshop, NIPS 2007. [pdf][bibtex]

S. Sabato and Y. Naveh, "Preprocessing expression-based constraint satisfaction problems for stochastic local search", Proceedings of CP-AI-OR, 2007. [pdf][bibtex]

S. Sabato, E. Yom-Tov, A. Tsherniak and S. Rosset, "Analyzing system logs: A new view of what's important", Proceedings of Second Workshop on Computer Systems with Machine Learning (SysML), 2007. [pdf][bibtex]

S. Sabato and Y. Winter, "Against partitioned readings of reciprocals", Proceedings of 15th Amsterdam Colloquium, 2005. [pdf][bibtex]

S. Sabato and Y. Winter, "From semantic restrictions to reciprocal meanings", Proceedings of Formal Grammar and Mathematics of Language (FG-MOL), 2005. [pdf][bibtex]

Book Chapters

S. Sabato and Y. Winter, "Against partitioned readings of reciprocals", In The Linguistics Enterprise, Edited by M. Everaert, T. Lentz, H. de Mulder, Ø. Nilsen and A. Zondervan. John Benjamins Publishing Company: 283-290, 2010. [bibtex]

Theses

S. Sabato, "Partial Information and Distribution-Dependence in Supervised Learning Models", Ph.D. Thesis, Supervised by Naftali Tishby, The Hebrew University, Jerusalem, June 2012. [pdf][bibtex]

S. Sabato, "The Interpretation of reciprocal expressions in natural language", M.Sc. Thesis, Supervised by Yoad Winter, Technion - Israel Institute of Technology, 2006. [bibtex]

Patents

S. Sabato and Y. Naveh, "Reformulation of constraint satisfaction problems for stochastic search", Issued patent US7587376.

S. Sabato, E. Yom-Tov and A. Tsherniak, "Apparatus for and Method of Implementing System Log Message Ranking via System Behavior Analysis", Issued Patent US8452761.

A. Tsherniak and S. Sabato, "A System and Method for Visualization of Time-Based Events", Issued Patent US8103966.

S. Sabato and T. Meltzer, "System Configuration Analysis", Issued Patent US8019987.

Other

S. Sabato, "Melody summarizes computer system descriptions automatically", IBM Innovation Matters web magazine, September 2007.