Prediction by Categorical Features: Generalization Properties and Application to Feature Ranking. - Sivan Sabato; Shai Shalev-Shwartz (COLT, 2007)

Preprocessing Expression-Based Constraint Satisfaction Problems for Stochastic Local Search. - Sivan Sabato; Yehuda Naveh (CPAIOR, 2007)

Ranking Categorical Features Using Generalization Properties. - Sivan Sabato; Shai Shalev-Shwartz (J. Mach. Learn. Res., 2008)

Homogeneous Multi-Instance Learning with Arbitrary Dependence. - Sivan Sabato; Naftali Tishby (COLT, 2009)

Tight Sample Complexity of Large-Margin Learning. - Sivan Sabato; Nathan Srebro; Naftali Tishby (NIPS, 2010)

Reducing Label Complexity by Learning From Bags. - Sivan Sabato; Nathan Srebro; Naftali Tishby (AISTATS, 2010)

Learning and generalization with the information bottleneck. - Ohad Shamir; Sivan Sabato; Naftali Tishby (Theor. Comput. Sci., 2010)

Active Learning Halfspaces under Margin Assumptions - Alon Gonen; Sivan Sabato; Shai Shalev-Shwartz (CoRR, 2011)

Multiclass Learnability and the ERM principle. - Amit Daniely; Sivan Sabato; Shai Ben-David; Shai Shalev-Shwartz (COLT, 2011)

Multiclass Learning Approaches: A Theoretical Comparison with Implications. - Amit Daniely; Sivan Sabato; Shai Shalev-Shwartz (NIPS, 2012)

Characterizing the Sample Complexity of Large-Margin Learning With Second-Order Statistics - Sivan Sabato; Nati Srebro; Naftali Tishby (CoRR, 2012)

Efficient Pool-Based Active Learning of Halfspaces - Alon Gonen; Sivan Sabato; Shai Shalev-Shwartz (CoRR, 2012)

Multi-instance learning with any hypothesis class. - Sivan Sabato; Naftali Tishby (J. Mach. Learn. Res., 2012)

Partial information and distribution-dependence in supervised learning models (שער נוסף בעברית: מידע חלקי ותלות בהתפלגות במודלים של למידה מונחית.). - Sivan Sabato (2012)

Clustering Oligarchies. - Margareta Ackerman; Shai Ben-David; David Loker; Sivan Sabato (AISTATS, 2013)

Feature Multi-Selection among Subjective Features. - Sivan Sabato; Adam Kalai (ICML (3), 2013)

Auditing: Active Learning with Outcome-Dependent Query Costs. - Sivan Sabato; Anand D. Sarwate; Nati Srebro (NIPS, 2013)

Approximate loss minimization with heavy tails. - Daniel J. Hsu; Sivan Sabato (CoRR, 2013)

Efficient active learning of halfspaces: an aggressive approach. - Alon Gonen; Sivan Sabato; Shai Shalev-Shwartz (J. Mach. Learn. Res., 2013)

Distribution-dependent sample complexity of large margin learning. - Sivan Sabato; Nathan Srebro; Naftali Tishby (J. Mach. Learn. Res., 2013)

Heavy-tailed regression with a generalized median-of-means. - Daniel J. Hsu; Sivan Sabato (ICML, 2014)

Active Regression by Stratification. - Sivan Sabato; Rémi Munos (NIPS, 2014)

Learning sparse low-threshold linear classifiers. - Sivan Sabato; Shai Shalev-Shwartz; Nathan Srebro; Daniel J. Hsu; Tong Zhang 001 (J. Mach. Learn. Res., 2015)

Interactive Algorithms: from Pool to Stream. - Sivan Sabato; Tom Hess (COLT, 2016)

Loss Minimization and Parameter Estimation with Heavy Tails. - Daniel J. Hsu; Sivan Sabato (J. Mach. Learn. Res., 2016)

Tunable Sensitivity to Large Errors in Neural Network Training. - Gil Keren; Sivan Sabato; Björn W. Schuller (AAAI, 2017)

Nearest-Neighbor Sample Compression: Efficiency, Consistency, Infinite Dimensions. - Aryeh Kontorovich; Sivan Sabato; Roi Weiss (NIPS, 2017)

The submodular secretary problem under a cardinality constraint and with limited resources. - Tom Hess; Sivan Sabato (CoRR, 2017)

Active Nearest-Neighbor Learning in Metric Spaces. - Aryeh Kontorovich; Sivan Sabato; Ruth Urner (J. Mach. Learn. Res., 2017)

Interactive Algorithms: Pool, Stream and Precognitive Stream. - Sivan Sabato; Tom Hess (J. Mach. Learn. Res., 2017)

Fast Single-Class Classification and the Principle of Logit Separation. - Gil Keren; Sivan Sabato; Björn W. Schuller (ICDM, 2018)

Learning from discriminative feature feedback. - Sanjoy Dasgupta; Akansha Dey; Nicholas Roberts; Sivan Sabato (NeurIPS, 2018)

Submodular learning and covering with response-dependent costs. - Sivan Sabato (Theor. Comput. Sci., 2018)

Temporal Anomaly Detection: Calibrating the Surprise. - Eyal Gutflaish; Aryeh Kontorovich; Sivan Sabato; Ofer Biller; Oded Sofer (AAAI, 2019)

A Walkthrough for the Principle of Logit Separation. - Gil Keren; Sivan Sabato; Björn W. Schuller (IJCAI, 2019)

Epsilon-Best-Arm Identification in Pay-Per-Reward Multi-Armed Bandits. - Sivan Sabato (NeurIPS, 2019)

BacPaCS - Bacterial Pathogenicity Classification via Sparse-SVM. - Eran Barash; Neta Sal-Man; Sivan Sabato; Michal Ziv-Ukelson (Bioinform., 2019)

Robust Learning from Discriminative Feature Feedback. - Sanjoy Dasgupta; Sivan Sabato (AISTATS, 2020)

Sequential no-Substitution k-Median-Clustering. - Tom Hess; Sivan Sabato (AISTATS, 2020)

Bounding the fairness and accuracy of classifiers from population statistics. - Sivan Sabato; Elad Yom-Tov (ICML, 2020)

Universal Bayes Consistency in Metric Spaces. - Steve Hanneke; Aryeh Kontorovich; Sivan Sabato; Roi Weiss (ITA, 2020)

Approximating a Target Distribution using Weight Queries. - Nadav Barak; Sivan Sabato (CoRR, 2020)

Analysis of loss functions for fast single-class classification. - Gil Keren; Sivan Sabato; Björn W. Schuller (Knowl. Inf. Syst., 2020)

Active Feature Selection for the Mutual Information Criterion. - Shachar Schnapp; Sivan Sabato (AAAI, 2021)

Approximating a Distribution Using Weight Queries. - Nadav Barak; Sivan Sabato (ICML, 2021)

A Constant Approximation Algorithm for Sequential Random-Order No-Substitution k-Median Clustering. - Tom Hess; Michal Moshkovitz; Sivan Sabato (NeurIPS, 2021)

A Constant Approximation Algorithm for Sequential No-Substitution k-Median Clustering under a Random Arrival Order. - Tom Hess; Michal Moshkovitz; Sivan Sabato (CoRR, 2021)

A Fast Algorithm for PAC Combinatorial Pure Exploration. - Noa Ben-David; Sivan Sabato (AAAI, 2022)

Inferring Unfairness and Error from Population Statistics in Binary and Multiclass Classification. - Sivan Sabato; Eran Treister; Elad Yom-Tov (CoRR, 2022)

Active Structure Learning of Bayesian Networks in an Observational Setting. - Noa Ben-David; Sivan Sabato (J. Mach. Learn. Res., 2022)

Fast Distributed k-Means with a Small Number of Rounds. - Tom Hess; Ron Visbord; Sivan Sabato (AISTATS, 2023)

Improved Robust Algorithms for Learning with Discriminative Feature Feedback. - Sivan Sabato (AISTATS, 2023)

On the Capacity Limits of Privileged ERM. - Michal Sharoni; Sivan Sabato (AISTATS, 2023)

Adaptive Combinatorial Maximization: Beyond Approximate Greedy Policies. - Shlomi Weitzman; Sivan Sabato (ALT, 2024)

Differentially Private Source-Target Clustering. - Shachar Schnapp; Sivan Sabato (Trans. Mach. Learn. Res., 2025)