Sivan Sabato

41 papers · 2008–2026 · 8 conferences · across top CS/AI conferences

Achievements

+11 more ↓

🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🗺️ Taxonomy Completionist (12) 🌍 Conference Polyglot (8)

🌈 Renaissance Researcher (8) 🧭 Keyword Pioneer 🏃 Academic Marathon (17) 🔬 Deep Specialist (18) 🏆 Keyword Champion (3) 💎 Century Club (40) 🗃️ Keyword Collector (62) 🔥 Unstoppable (16) 📈 Trend Setter 🚀 Conference Pioneer ⚡ Prolific Year (6)

Conferences

JMLR (10) NIPS (9) AISTATS (7) ICML (6) AAAI (3) ALT (3) COLT (2) IJCAI (1)

Top co-authors

Shai Shalev-shwartz (6) Tom Hess (5) Aryeh Kontorovich (4) Naftali Tishby (4) Nathan Srebro (4) Amit Daniely (3) Daniel Hsu (3) Shai Ben-David (3) Sanjoy Dasgupta (2) Noa Ben-David (2)

Keywords

active learning (11) sample complexity (9) label complexity (6) online learning (5) multiclass classification (4) binary classification (4) learning theory (3) metric space (3) linear regression (3) empirical risk minimization (3) sample compression (3) query complexity (3) nearest neighbor (2) k-means clustering (2) vc dimension (2) multi-class classification (2) statistical learning (2) margin-based learning (2) theoretical analysis (2) interactive learning (2)

Papers

Discriminative Feature Feedback with General Teacher Classes ALT 2026 Disparate Conditional Prediction in Multiclass Classifiers ICML 2025 Adaptive Combinatorial Maximization: Beyond Approximate Greedy Policies ALT 2024 Improved Robust Algorithms for Learning with Discriminative Feature Feedback AISTATS 2023 Fast Distributed k-Means with a Small Number of Rounds AISTATS 2023 On the Capacity Limits of Privileged ERM AISTATS 2023 Active Structure Learning of Bayesian Networks in an Observational Setting JMLR 2022 A Fast Algorithm for PAC Combinatorial Pure Exploration AAAI 2022 Active Feature Selection for the Mutual Information Criterion AAAI 2021 A Constant Approximation Algorithm for Sequential Random-Order No-Substitution k-Median Clustering NIPS 2021 Approximating a Distribution Using Weight Queries ICML 2021 Algorithmic Learning Theory 2021: Preface ALT 2021 Robust Learning from Discriminative Feature Feedback AISTATS 2020 Bounding the fairness and accuracy of classifiers from population statistics ICML 2020 Sequential no-Substitution k-Median-Clustering AISTATS 2020 Epsilon-Best-Arm Identification in Pay-Per-Reward Multi-Armed Bandits NIPS 2019 A Walkthrough for the Principle of Logit Separation IJCAI 2019 Temporal Anomaly Detection: Calibrating the Surprise AAAI 2019 Active Nearest-Neighbor Learning in Metric Spaces JMLR 2018 Learning from discriminative feature feedback NIPS 2018 Interactive Algorithms: Pool, Stream and Precognitive Stream JMLR 2018 Nearest-Neighbor Sample Compression: Efficiency, Consistency, Infinite Dimensions NIPS 2017 Interactive Algorithms: from Pool to Stream COLT 2016 Loss Minimization and Parameter Estimation with Heavy Tails JMLR 2016 Active Nearest-Neighbor Learning in Metric Spaces NIPS 2016 Multiclass Learnability and the ERM Principle JMLR 2015 Learning Sparse Low-Threshold Linear Classifiers JMLR 2015 Active Regression by Stratification NIPS 2014 Heavy-tailed regression with a generalized median-of-means ICML 2014 Feature Multi-Selection among Subjective Features ICML 2013 Clustering Oligarchies AISTATS 2013 Distribution-Dependent Sample Complexity of Large Margin Learning JMLR 2013 Efficient Active Learning of Halfspaces: An Aggressive Approach JMLR 2013 Efficient Active Learning of Halfspaces: an Aggressive Approach ICML 2013 Auditing: Active Learning with Outcome-Dependent Query Costs NIPS 2013 Multiclass Learning Approaches: A Theoretical Comparison with Implications NIPS 2012 Multi-Instance Learning with Any Hypothesis Class JMLR 2012 Multiclass Learnability and the ERM principle COLT 2011 Tight Sample Complexity of Large-Margin Learning NIPS 2010 Reducing Label Complexity by Learning From Bags AISTATS 2010 Ranking Categorical Features Using Generalization Properties JMLR 2008