Preprints
A. Gonen, S. Sabato and S. Shalev-Shwartz "Active Learning of Halfspaces under Margin Assumptions", ArXiv:1112.1556, 2011.S. Sabato and N. Tishby, "Multi-Instance Learning with Any Hypothesis Class", ArXiv:117.2021, 2011.
S. Sabato, N. Srebro and N. Tishby, "Characterizing the Sample Complexity of Large-Margin Learning With Second-Order Statistics", ArXiv:1204.1276, 2012.
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.Journal Papers
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. [direct link][local pdf]S. Sabato, S. Shalev-Shwartz "Ranking Categorical Features Using Generalization Properties", Journal of Machine Learning Research, 9(Jun):1083-1114, 2008. [pdf]
Conferences
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]S. Sabato, N. Srebro and N. Tishby, "Tight Sample Complexity of Large-Margin Learning", Neural Information Processing Systems 23 (NIPS), 2010. [full version, with corrections]
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 [full version].
S. Sabato, N. Tishby, "Homogeneous Multi-Instance Learning with Arbitrary Dependence", Proceedings of The Twenty Second Annual Conference on Learning Theory (COLT), 2009. [pdf]
O. Shamir, S. Sabato, and N. Tishby, "Learning and Generalization with the Information Bottleneck", Proceedings of Algorithmic Learning Theory (ALT) 2008.[pdf] [full version]
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] [full version]
S. Sabato, E. Yom-Tov, and O. Rodeh, "Melody - Expert-Free System Analysis", Machine Learning for Systems Problems Workshop, NIPS 2007. [pdf]
S. Sabato and Y. Naveh, "Preprocessing expression-based constraint satisfaction problems for stochastic local search", Proceedings of CP-AI-OR, 2007. [pdf]
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]
S. Sabato and Y. Winter, "Against partitioned readings of reciprocals", Proceedings of 15th Amsterdam Colloquium, 2005.[pdf]
S. Sabato and Y. Winter, "From semantic restrictions to reciprocal meanings", Proceedings of Formal Grammar and Mathematics of Language (FG-MOL), 2005.[pdf]
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", U.S Patent request 11/877679.
A. Tsherniak and S. Sabato, "A System and Method for Visualization of Time-Based Events", US Patent Request 12/025776.
S. Sabato and T. Meltzer, "System Configuration Analysis", US Patent Request 12/028838.
Invited Talks
S. Sabato, "Melody - Reducing warranty costs of xServers using machine learning", IBM Academy of Technology 5th Proactive Problem Prediction, Avoidance, and Diagnosis Conference, April 2007.S. Sabato, "Feature Selection for Categorical Features with Many Values", IBM Haifa Machine Learning Seminar, May 2007.