Sivan Sabato

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 52

Top Topics

Loss Minimization

Information Criterion

Structure Learning

Top Venues

J. Mach. Learn. Res.

Publications

Shlomi Weitzman, Sivan Sabato
Adaptive Combinatorial Maximization: Beyond Approximate Greedy Policies. CoRR (2024)
Shlomi Weitzman, Sivan Sabato
Adaptive Combinatorial Maximization: Beyond Approximate Greedy Policies. ALT (2024)
Michal Sharoni, Sivan Sabato
On the Capacity Limits of Privileged ERM. CoRR (2023)
Tom Hess, Ron Visbord, Sivan Sabato
Fast Distributed k-Means with a Small Number of Rounds. AISTATS (2023)
Sivan Sabato
Improved Robust Algorithms for Learning with Discriminative Feature Feedback. AISTATS (2023)
Michal Sharoni, Sivan Sabato
On the Capacity Limits of Privileged ERM. AISTATS (2023)
Sivan Sabato
Improved Robust Algorithms for Learning with Discriminative Feature Feedback. CoRR (2022)
Noa Ben-David, Sivan Sabato
Active Structure Learning of Bayesian Networks in an Observational Setting. J. Mach. Learn. Res. 23 (2022)
Tom Hess, Ron Visbord, Sivan Sabato
Fast Distributed k-Means with a Small Number of Rounds. CoRR (2022)
Sivan Sabato, Eran Treister, Elad Yom-Tov
Inferring Unfairness and Error from Population Statistics in Binary and Multiclass Classification. CoRR (2022)
Noa Ben-David, Sivan Sabato
A Fast Algorithm for PAC Combinatorial Pure Exploration. AAAI (2022)
Tom Hess, Michal Moshkovitz, Sivan Sabato
A Constant Approximation Algorithm for Sequential Random-Order No-Substitution k-Median Clustering. NeurIPS (2021)
Noa Ben-David, Sivan Sabato
Active Structure Learning of Bayesian Networks in an Observational Setting. CoRR (2021)
Shachar Schnapp, Sivan Sabato
Active Feature Selection for the Mutual Information Criterion. AAAI (2021)
Tom Hess, Michal Moshkovitz, Sivan Sabato
A Constant Approximation Algorithm for Sequential No-Substitution k-Median Clustering under a Random Arrival Order. CoRR (2021)
Noa Ben-David, Sivan Sabato
A Fast Algorithm for PAC Combinatorial Pure Exploration. CoRR (2021)
Nadav Barak, Sivan Sabato
Approximating a Distribution Using Weight Queries. ICML (2021)
Tom Hess, Sivan Sabato
Sequential no-Substitution k-Median-Clustering. AISTATS (2020)
Gil Keren, Sivan Sabato, Björn W. Schuller
Analysis of loss functions for fast single-class classification. Knowl. Inf. Syst. 62 (1) (2020)
Nadav Barak, Sivan Sabato
Approximating a Target Distribution using Weight Queries. CoRR (2020)
Shachar Schnapp, Sivan Sabato
Active Feature Selection for the Mutual Information Criterion. CoRR (2020)
Sivan Sabato, Elad Yom-Tov
Bounding the fairness and accuracy of classifiers from population statistics. ICML (2020)
Sanjoy Dasgupta, Sivan Sabato
Robust Learning from Discriminative Feature Feedback. AISTATS (2020)
Sanjoy Dasgupta, Sivan Sabato
Robust Learning from Discriminative Feature Feedback. CoRR (2020)
Steve Hanneke, Aryeh Kontorovich, Sivan Sabato, Roi Weiss
Universal Bayes Consistency in Metric Spaces. ITA (2020)
Eran Barash, Neta Sal-Man, Sivan Sabato, Michal Ziv-Ukelson
BacPaCS - Bacterial Pathogenicity Classification via Sparse-SVM. Bioinform. 35 (12) (2019)
Eyal Gutflaish, Aryeh Kontorovich, Sivan Sabato, Ofer Biller, Oded Sofer
Temporal Anomaly Detection: Calibrating the Surprise. AAAI (2019)
Gil Keren, Sivan Sabato, Björn W. Schuller
A Walkthrough for the Principle of Logit Separation. IJCAI (2019)
Steve Hanneke, Aryeh Kontorovich, Sivan Sabato, Roi Weiss
Universal Bayes consistency in metric spaces. CoRR (2019)
Sivan Sabato
Epsilon-Best-Arm Identification in Pay-Per-Reward Multi-Armed Bandits. NeurIPS (2019)
Tom Hess, Sivan Sabato
Sequential no-Substitution k-Median-Clustering. CoRR (2019)
Sanjoy Dasgupta, Akansha Dey, Nicholas Roberts, Sivan Sabato
Learning from discriminative feature feedback. NeurIPS (2018)
Gil Keren, Sivan Sabato, Björn W. Schuller
Fast Single-Class Classification and the Principle of Logit Separation. ICDM (2018)
Sivan Sabato
Submodular learning and covering with response-dependent costs. Theor. Comput. Sci. 742 (2018)
Aryeh Kontorovich, Sivan Sabato, Roi Weiss
Nearest-Neighbor Sample Compression: Efficiency, Consistency, Infinite Dimensions. NIPS (2017)
Aryeh Kontorovich, Sivan Sabato, Roi Weiss
Nearest-Neighbor Sample Compression: Efficiency, Consistency, Infinite Dimensions. CoRR (2017)
Gil Keren, Sivan Sabato, Björn W. Schuller
Fast Single-Class Classification and the Principle of Logit Separation. CoRR (2017)
Tom Hess, Sivan Sabato
The submodular secretary problem under a cardinality constraint and with limited resources. CoRR (2017)
Eyal Gutflaish, Aryeh Kontorovich, Sivan Sabato, Ofer Biller, Oded Sofer
Temporal anomaly detection: calibrating the surprise. CoRR (2017)
Sivan Sabato, Tom Hess
Interactive Algorithms: Pool, Stream and Precognitive Stream. J. Mach. Learn. Res. 18 (2017)
Aryeh Kontorovich, Sivan Sabato, Ruth Urner
Active Nearest-Neighbor Learning in Metric Spaces. J. Mach. Learn. Res. 18 (2017)
Gil Keren, Sivan Sabato, Björn W. Schuller
Tunable Sensitivity to Large Errors in Neural Network Training. AAAI (2017)
Sivan Sabato, Tom Hess
Interactive algorithms: From pool to stream. CoRR (2016)
Sivan Sabato, Tom Hess
Interactive Algorithms: from Pool to Stream. COLT (2016)
Gil Keren, Sivan Sabato, Björn W. Schuller
Tunable Sensitivity to Large Errors in Neural Network Training. CoRR (2016)
Aryeh Kontorovich, Sivan Sabato, Ruth Urner
Active Nearest-Neighbor Learning in Metric Spaces. CoRR (2016)
Aryeh Kontorovich, Sivan Sabato, Ruth Urner
Active Nearest-Neighbor Learning in Metric Spaces. NIPS (2016)
Sivan Sabato
Submodular Learning and Covering with Response-Dependent Costs. ALT (2016)
Daniel J. Hsu, Sivan Sabato
Loss Minimization and Parameter Estimation with Heavy Tails. J. Mach. Learn. Res. 17 (2016)
Sivan Sabato
Submodular Learning and Covering with Response-Dependent Costs. CoRR (2016)
Sivan Sabato, Shai Shalev-Shwartz, Nathan Srebro, Daniel J. Hsu, Tong Zhang
Learning sparse low-threshold linear classifiers. J. Mach. Learn. Res. 16 (2015)
Amit Daniely, Sivan Sabato, Shai Ben-David, Shai Shalev-Shwartz
Multiclass learnability and the ERM principle. J. Mach. Learn. Res. 16 (2015)
Daniel J. Hsu, Sivan Sabato
Heavy-tailed regression with a generalized median-of-means. ICML (2014)
Sivan Sabato, Rémi Munos
Active Regression by Stratification. NIPS (2014)
Sivan Sabato, Rémi Munos
Active Regression by Stratification. CoRR (2014)
Alon Gonen, Sivan Sabato, Shai Shalev-Shwartz
Efficient Active Learning of Halfspaces: an Aggressive Approach. ICML (1) (2013)
Daniel J. Hsu, Sivan Sabato
Approximate loss minimization with heavy tails. CoRR (2013)
Sivan Sabato, Adam Kalai
Feature Multi-Selection among Subjective Features. ICML (3) (2013)
Sivan Sabato, Nathan Srebro, Naftali Tishby
Distribution-dependent sample complexity of large margin learning. J. Mach. Learn. Res. 14 (1) (2013)
Sivan Sabato, Anand D. Sarwate, Nati Srebro
Auditing: Active Learning with Outcome-Dependent Query Costs. NIPS (2013)
Sivan Sabato, Anand D. Sarwate, Nathan Srebro
Auditing: Active Learning with Outcome-Dependent Query Costs. CoRR (2013)
Amit Daniely, Sivan Sabato, Shai Ben-David, Shai Shalev-Shwartz
Multiclass learnability and the ERM principle. CoRR (2013)
Alon Gonen, Sivan Sabato, Shai Shalev-Shwartz
Efficient active learning of halfspaces: an aggressive approach. J. Mach. Learn. Res. 14 (1) (2013)
Sivan Sabato, Adam Kalai
Feature Multi-Selection among Subjective Features CoRR (2013)
Margareta Ackerman, Shai Ben-David, David Loker, Sivan Sabato
Clustering Oligarchies. AISTATS (2013)
Sivan Sabato, Nati Srebro, Naftali Tishby
Characterizing the Sample Complexity of Large-Margin Learning With Second-Order Statistics CoRR (2012)
Alon Gonen, Sivan Sabato, Shai Shalev-Shwartz
Efficient Pool-Based Active Learning of Halfspaces CoRR (2012)
Sivan Sabato, Shai Shalev-Shwartz, Nathan Srebro, Daniel J. Hsu, Tong Zhang
Learning Sparse Low-Threshold Linear Classifiers CoRR (2012)
Amit Daniely, Sivan Sabato, Shai Shalev-Shwartz
Multiclass Learning Approaches: A Theoretical Comparison with Implications. NIPS (2012)
Sivan Sabato, Naftali Tishby
Multi-instance learning with any hypothesis class. J. Mach. Learn. Res. 13 (2012)
Amit Daniely, Sivan Sabato, Shai Shalev-Shwartz
Multiclass Learning Approaches: A Theoretical Comparison with Implications CoRR (2012)
Alon Gonen, Sivan Sabato, Shai Shalev-Shwartz
Active Learning Halfspaces under Margin Assumptions CoRR (2011)
Amit Daniely, Sivan Sabato, Shai Ben-David, Shai Shalev-Shwartz
Multiclass Learnability and the ERM principle. COLT (2011)
Sivan Sabato, Naftali Tishby
Multi-Instance Learning with Any Hypothesis Class CoRR (2011)
Sivan Sabato, Nathan Srebro, Naftali Tishby
Tight Sample Complexity of Large-Margin Learning. NIPS (2010)
Ohad Shamir, Sivan Sabato, Naftali Tishby
Learning and generalization with the information bottleneck. Theor. Comput. Sci. 411 (29-30) (2010)
Sivan Sabato, Nathan Srebro, Naftali Tishby
Tight Sample Complexity of Large-Margin Learning CoRR (2010)
Sivan Sabato, Nathan Srebro, Naftali Tishby
Reducing Label Complexity by Learning From Bags. AISTATS (2010)
Sivan Sabato, Naftali Tishby
Homogeneous Multi-Instance Learning with Arbitrary Dependence. COLT (2009)
Sivan Sabato, Shai Shalev-Shwartz
Ranking Categorical Features Using Generalization Properties. J. Mach. Learn. Res. 9 (2008)
Ohad Shamir, Sivan Sabato, Naftali Tishby
Learning and Generalization with the Information Bottleneck. ALT (2008)
Sivan Sabato, Shai Shalev-Shwartz
Prediction by Categorical Features: Generalization Properties and Application to Feature Ranking. COLT (2007)
Sivan Sabato, Yehuda Naveh
Preprocessing Expression-Based Constraint Satisfaction Problems for Stochastic Local Search. CPAIOR (2007)