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ORCIDSivan Sabato
Person information
- affiliation: McMaster University, Ontario, Canada
- affiliation (former): Ben Gurion University of the Negev, Israel
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2020 – today
- 2024
[c36]Shlomi Weitzman, Sivan Sabato:
Adaptive Combinatorial Maximization: Beyond Approximate Greedy Policies. ALT 2024: 1188-1207- [i33]Shlomi Weitzman, Sivan Sabato:
Adaptive Combinatorial Maximization: Beyond Approximate Greedy Policies. CoRR abs/2404.01930 (2024) - 2023
- [c35]Michal Sharoni, Sivan Sabato:
On the Capacity Limits of Privileged ERM. AISTATS 2023: 523-534 - [c34]Tom Hess, Ron Visbord, Sivan Sabato:
Fast Distributed k-Means with a Small Number of Rounds. AISTATS 2023: 850-874 - [c33]Sivan Sabato:
Improved Robust Algorithms for Learning with Discriminative Feature Feedback. AISTATS 2023: 1024-1036 - [e3]Andreas Krause, Emma Brunskill, Kyunghyun Cho, Barbara Engelhardt, Sivan Sabato, Jonathan Scarlett:
International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA. Proceedings of Machine Learning Research 202, PMLR 2023 [contents] - [i32]Michal Sharoni, Sivan Sabato:
On the Capacity Limits of Privileged ERM. CoRR abs/2303.02658 (2023) - 2022
- [j14]Noa Ben-David, Sivan Sabato:
Active Structure Learning of Bayesian Networks in an Observational Setting. J. Mach. Learn. Res. 23: 188:1-188:38 (2022) - [c32]Noa Ben-David, Sivan Sabato:
A Fast Algorithm for PAC Combinatorial Pure Exploration. AAAI 2022: 6064-6071 - [e2]Kamalika Chaudhuri, Stefanie Jegelka, Le Song, Csaba Szepesvári, Gang Niu, Sivan Sabato:
International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA. Proceedings of Machine Learning Research 162, PMLR 2022 [contents] - [i31]Tom Hess, Ron Visbord, Sivan Sabato:
Fast Distributed k-Means with a Small Number of Rounds. CoRR abs/2201.13217 (2022) - [i30]Sivan Sabato, Eran Treister, Elad Yom-Tov:
Inferring Unfairness and Error from Population Statistics in Binary and Multiclass Classification. CoRR abs/2206.03234 (2022) - [i29]Sivan Sabato:
Improved Robust Algorithms for Learning with Discriminative Feature Feedback. CoRR abs/2209.03753 (2022) - 2021
- [c31]Shachar Schnapp, Sivan Sabato:
Active Feature Selection for the Mutual Information Criterion. AAAI 2021: 9497-9504 - [c30]Nadav Barak, Sivan Sabato:
Approximating a Distribution Using Weight Queries. ICML 2021: 674-683 - [c29]Tom Hess, Michal Moshkovitz, Sivan Sabato:
A Constant Approximation Algorithm for Sequential Random-Order No-Substitution k-Median Clustering. NeurIPS 2021: 3298-3308 - [e1]Vitaly Feldman, Katrina Ligett, Sivan Sabato:
Algorithmic Learning Theory, 16-19 March 2021, Virtual Conference, Worldwide. Proceedings of Machine Learning Research 132, PMLR 2021 [contents] - [i28]Tom Hess, Michal Moshkovitz, Sivan Sabato:
A Constant Approximation Algorithm for Sequential No-Substitution k-Median Clustering under a Random Arrival Order. CoRR abs/2102.04050 (2021) - [i27]Noa Ben-David, Sivan Sabato:
Active Structure Learning of Bayesian Networks in an Observational Setting. CoRR abs/2103.13796 (2021) - [i26]Noa Ben-David, Sivan Sabato:
A Fast Algorithm for PAC Combinatorial Pure Exploration. CoRR abs/2112.04197 (2021) - 2020
- [j13]Gil Keren
, Sivan Sabato, Björn W. Schuller:
Analysis of loss functions for fast single-class classification. Knowl. Inf. Syst. 62(1): 337-358 (2020) - [c28]Tom Hess, Sivan Sabato:
Sequential no-Substitution k-Median-Clustering. AISTATS 2020: 962-972 - [c27]Sanjoy Dasgupta, Sivan Sabato:
Robust Learning from Discriminative Feature Feedback. AISTATS 2020: 973-982 - [c26]Sivan Sabato, Elad Yom-Tov:
Bounding the fairness and accuracy of classifiers from population statistics. ICML 2020: 8316-8325 - [c25]Steve Hanneke, Aryeh Kontorovich, Sivan Sabato, Roi Weiss:
Universal Bayes Consistency in Metric Spaces. ITA 2020: 1-33 - [i25]Sanjoy Dasgupta, Sivan Sabato:
Robust Learning from Discriminative Feature Feedback. CoRR abs/2003.03946 (2020) - [i24]Nadav Barak, Sivan Sabato:
Approximating a Target Distribution using Weight Queries. CoRR abs/2006.13636 (2020) - [i23]Shachar Schnapp, Sivan Sabato:
Active Feature Selection for the Mutual Information Criterion. CoRR abs/2012.06979 (2020)
2010 – 2019
- 2019
- [j12]Eran Barash, Neta Sal-Man, Sivan Sabato, Michal Ziv-Ukelson:
BacPaCS - Bacterial Pathogenicity Classification via Sparse-SVM. Bioinform. 35(12): 2001-2008 (2019) - [c24]Eyal Gutflaish, Aryeh Kontorovich, Sivan Sabato, Ofer Biller, Oded Sofer:
Temporal Anomaly Detection: Calibrating the Surprise. AAAI 2019: 3755-3762 - [c23]Gil Keren, Sivan Sabato, Björn W. Schuller:
A Walkthrough for the Principle of Logit Separation. IJCAI 2019: 6191-6195 - [c22]Sivan Sabato:
Epsilon-Best-Arm Identification in Pay-Per-Reward Multi-Armed Bandits. NeurIPS 2019: 2876-2886 - [i22]Tom Hess, Sivan Sabato:
Sequential no-Substitution k-Median-Clustering. CoRR abs/1905.12925 (2019) - [i21]Steve Hanneke, Aryeh Kontorovich, Sivan Sabato, Roi Weiss:
Universal Bayes consistency in metric spaces. CoRR abs/1906.09855 (2019) - 2018
- [j11]Sivan Sabato:
Submodular learning and covering with response-dependent costs. Theor. Comput. Sci. 742: 98-113 (2018) - [c21]Gil Keren, Sivan Sabato, Björn W. Schuller:
Fast Single-Class Classification and the Principle of Logit Separation. ICDM 2018: 227-236 - [c20]Sanjoy Dasgupta, Akansha Dey, Nicholas Roberts, Sivan Sabato:
Learning from discriminative feature feedback. NeurIPS 2018: 3959-3967 - 2017
- [j10]Aryeh Kontorovich, Sivan Sabato, Ruth Urner:
Active Nearest-Neighbor Learning in Metric Spaces. J. Mach. Learn. Res. 18: 195:1-195:38 (2017) - [j9]Sivan Sabato, Tom Hess:
Interactive Algorithms: Pool, Stream and Precognitive Stream. J. Mach. Learn. Res. 18: 229:1-229:39 (2017) - [c19]Gil Keren, Sivan Sabato, Björn W. Schuller:
Tunable Sensitivity to Large Errors in Neural Network Training. AAAI 2017: 2087-2093 - [c18]Aryeh Kontorovich, Sivan Sabato, Roi Weiss:
Nearest-Neighbor Sample Compression: Efficiency, Consistency, Infinite Dimensions. NIPS 2017: 1573-1583 - [i20]Tom Hess, Sivan Sabato:
The submodular secretary problem under a cardinality constraint and with limited resources. CoRR abs/1702.03989 (2017) - [i19]Aryeh Kontorovich, Sivan Sabato, Roi Weiss:
Nearest-Neighbor Sample Compression: Efficiency, Consistency, Infinite Dimensions. CoRR abs/1705.08184 (2017) - [i18]Eyal Gutflaish, Aryeh Kontorovich, Sivan Sabato, Ofer Biller, Oded Sofer:
Temporal anomaly detection: calibrating the surprise. CoRR abs/1705.10085 (2017) - [i17]Gil Keren, Sivan Sabato, Björn W. Schuller:
Fast Single-Class Classification and the Principle of Logit Separation. CoRR abs/1705.10246 (2017) - 2016
- [j8]Daniel J. Hsu, Sivan Sabato:
Loss Minimization and Parameter Estimation with Heavy Tails. J. Mach. Learn. Res. 17: 18:1-18:40 (2016) - [c17]Sivan Sabato:
Submodular Learning and Covering with Response-Dependent Costs. ALT 2016: 130-144 - [c16]Sivan Sabato, Tom Hess:
Interactive Algorithms: from Pool to Stream. COLT 2016: 1419-1439 - [c15]Aryeh Kontorovich, Sivan Sabato, Ruth Urner:
Active Nearest-Neighbor Learning in Metric Spaces. NIPS 2016: 856-864 - [i16]Sivan Sabato, Tom Hess:
Interactive algorithms: From pool to stream. CoRR abs/1602.01132 (2016) - [i15]Sivan Sabato:
Submodular Learning and Covering with Response-Dependent Costs. CoRR abs/1602.07120 (2016) - [i14]Aryeh Kontorovich, Sivan Sabato, Ruth Urner:
Active Nearest-Neighbor Learning in Metric Spaces. CoRR abs/1605.06792 (2016) - [i13]Gil Keren, Sivan Sabato, Björn W. Schuller:
Tunable Sensitivity to Large Errors in Neural Network Training. CoRR abs/1611.07743 (2016) - 2015
- [j7]Sivan Sabato, Shai Shalev-Shwartz, Nathan Srebro, Daniel J. Hsu, Tong Zhang:
Learning sparse low-threshold linear classifiers. J. Mach. Learn. Res. 16: 1275-1304 (2015) - [j6]Amit Daniely, Sivan Sabato, Shai Ben-David, Shai Shalev-Shwartz:
Multiclass learnability and the ERM principle. J. Mach. Learn. Res. 16: 2377-2404 (2015) - 2014
- [c14]Daniel J. Hsu, Sivan Sabato:
Heavy-tailed regression with a generalized median-of-means. ICML 2014: 37-45 - [c13]Sivan Sabato, Rémi Munos:
Active Regression by Stratification. NIPS 2014: 469-477 - [i12]Sivan Sabato, Rémi Munos:
Active Regression by Stratification. CoRR abs/1410.5920 (2014) - 2013
- [j5]Sivan Sabato, Nathan Srebro, Naftali Tishby:
Distribution-dependent sample complexity of large margin learning. J. Mach. Learn. Res. 14(1): 2119-2149 (2013) - [j4]Alon Gonen, Sivan Sabato, Shai Shalev-Shwartz:
Efficient active learning of halfspaces: an aggressive approach. J. Mach. Learn. Res. 14(1): 2583-2615 (2013) - [c12]Margareta Ackerman, Shai Ben-David, David Loker, Sivan Sabato:
Clustering Oligarchies. AISTATS 2013: 66-74 - [c11]Alon Gonen, Sivan Sabato, Shai Shalev-Shwartz:
Efficient Active Learning of Halfspaces: an Aggressive Approach. ICML (1) 2013: 480-488 - [c10]Sivan Sabato, Adam Kalai:
Feature Multi-Selection among Subjective Features. ICML (3) 2013: 810-818 - [c9]Sivan Sabato, Anand D. Sarwate, Nati Srebro:
Auditing: Active Learning with Outcome-Dependent Query Costs. NIPS 2013: 512-520 - [i11]Sivan Sabato, Adam Kalai:
Feature Multi-Selection among Subjective Features. CoRR abs/1302.4297 (2013) - [i10]Sivan Sabato, Anand D. Sarwate, Nathan Srebro:
Auditing: Active Learning with Outcome-Dependent Query Costs. CoRR abs/1306.2347 (2013) - [i9]Daniel J. Hsu, Sivan Sabato:
Approximate loss minimization with heavy tails. CoRR abs/1307.1827 (2013) - [i8]Amit Daniely, Sivan Sabato, Shai Ben-David, Shai Shalev-Shwartz:
Multiclass learnability and the ERM principle. CoRR abs/1308.2893 (2013) - 2012
- [b1]Sivan Sabato:
Partial information and distribution-dependence in supervised learning models (שער נוסף בעברית: מידע חלקי ותלות בהתפלגות במודלים של למידה מונחית.). Hebrew University of Jerusalem, Israel, 2012 - [j3]Sivan Sabato, Naftali Tishby:
Multi-instance learning with any hypothesis class. J. Mach. Learn. Res. 13: 2999-3039 (2012) - [c8]Amit Daniely, Sivan Sabato, Shai Shalev-Shwartz:
Multiclass Learning Approaches: A Theoretical Comparison with Implications. NIPS 2012: 494-502 - [i7]Sivan Sabato, Nati Srebro, Naftali Tishby:
Characterizing the Sample Complexity of Large-Margin Learning With Second-Order Statistics. CoRR abs/1204.1276 (2012) - [i6]Amit Daniely, Sivan Sabato, Shai Shalev-Shwartz:
Multiclass Learning Approaches: A Theoretical Comparison with Implications. CoRR abs/1205.6432 (2012) - [i5]Alon Gonen, Sivan Sabato, Shai Shalev-Shwartz:
Efficient Pool-Based Active Learning of Halfspaces. CoRR abs/1208.3561 (2012) - [i4]Sivan Sabato, Shai Shalev-Shwartz, Nathan Srebro, Daniel J. Hsu, Tong Zhang:
Learning Sparse Low-Threshold Linear Classifiers. CoRR abs/1212.3276 (2012) - 2011
- [c7]Amit Daniely, Sivan Sabato, Shai Ben-David, Shai Shalev-Shwartz:
Multiclass Learnability and the ERM principle. COLT 2011: 207-232 - [i3]Sivan Sabato, Naftali Tishby:
Multi-Instance Learning with Any Hypothesis Class. CoRR abs/1107.2021 (2011) - [i2]Alon Gonen, Sivan Sabato, Shai Shalev-Shwartz:
Active Learning Halfspaces under Margin Assumptions. CoRR abs/1112.1556 (2011) - 2010
- [j2]Ohad Shamir, Sivan Sabato, Naftali Tishby:
Learning and generalization with the information bottleneck. Theor. Comput. Sci. 411(29-30): 2696-2711 (2010) - [c6]Sivan Sabato, Nathan Srebro, Naftali Tishby:
Tight Sample Complexity of Large-Margin Learning. NIPS 2010: 2038-2046 - [c5]Sivan Sabato, Nathan Srebro, Naftali Tishby:
Reducing Label Complexity by Learning From Bags. AISTATS 2010: 685-692 - [i1]Sivan Sabato, Nathan Srebro, Naftali Tishby:
Tight Sample Complexity of Large-Margin Learning. CoRR abs/1011.5053 (2010)
2000 – 2009
- 2009
- [c4]Sivan Sabato, Naftali Tishby:
Homogeneous Multi-Instance Learning with Arbitrary Dependence. COLT 2009 - 2008
- [j1]Sivan Sabato, Shai Shalev-Shwartz:
Ranking Categorical Features Using Generalization Properties. J. Mach. Learn. Res. 9: 1083-1114 (2008) - [c3]Ohad Shamir, Sivan Sabato, Naftali Tishby:
Learning and Generalization with the Information Bottleneck. ALT 2008: 92-107 - 2007
- [c2]Sivan Sabato, Shai Shalev-Shwartz:
Prediction by Categorical Features: Generalization Properties and Application to Feature Ranking. COLT 2007: 559-573 - [c1]Sivan Sabato, Yehuda Naveh:
Preprocessing Expression-Based Constraint Satisfaction Problems for Stochastic Local Search. CPAIOR 2007: 244-259
Coauthor Index
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last updated on 2024-10-17 21:32 CEST by the dblp team
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