Mansour, Yishay

187 publications

COLT 2025 A Fine-Grained Characterization of PAC Learnability Marco Bressan, Nataly Brukhim, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen

AAAI 2025 Batch Ensemble for Variance Dependent Regret in Stochastic Bandits Asaf B. Cassel, Orin Levy, Yishay Mansour

ICML 2025 Convergence of Policy Mirror Descent Beyond Compatible Function Approximation Uri Sherman, Tomer Koren, Yishay Mansour

AAAI 2025 Delay as Payoff in MAB Ofir Schlisselberg, Ido Cohen, Tal Lancewicki, Yishay Mansour

ICML 2025 Dueling Convex Optimization with General Preferences Aadirupa Saha, Tomer Koren, Yishay Mansour

NeurIPS 2025 Improved Best-of-Both-Worlds Regret for Bandits with Delayed Feedback Ofir Schlisselberg, Tal Lancewicki, Peter Auer, Yishay Mansour

NeurIPS 2025 Individual Regret in Cooperative Stochastic Multi-Armed Bandits Idan Barnea, Tal Lancewicki, Yishay Mansour

ICML 2025 Near-Optimal Regret Using Policy Optimization in Online MDPs with Aggregate Bandit Feedback Tal Lancewicki, Yishay Mansour

ALT 2025 Non-Stochastic Bandits with Evolving Observations Yogev Bar-On, Yishay Mansour

COLT 2025 Of Dice and Games: A Theory of Generalized Boosting Marco Bressan, Nataly Brukhim, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen

NeurIPS 2025 Principled Model Routing for Unknown Mixtures of Source Domains Christoph Dann, Yishay Mansour, Teodor Vanislavov Marinov, Mehryar Mohri

NeurIPS 2025 Probably Approximately Precision and Recall Learning Lee Cohen, Yishay Mansour, Shay Moran, Han Shao

COLT 2025 Rate-Preserving Reductions for Blackwell Approachability Christoph Dann, Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan

NeurIPS 2025 Regret Bounds for Adversarial Contextual Bandits with General Function Approximation and Delayed Feedback Orin Levy, Liad Erez, Alon Cohen, Yishay Mansour

COLT 2024 A Theory of Interpretable Approximations Marco Bressan, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen

NeurIPSW 2024 A Theory of Interpretable Approximations Marco Bressan, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen

NeurIPSW 2024 Domain Adaptation for Robust Model Routing Christoph Dann, Yishay Mansour, Teodor Vanislavov Marinov, Mehryar Mohri

ICML 2024 Eluder-Based Regret for Stochastic Contextual MDPs Orin Levy, Asaf Cassel, Alon Cohen, Yishay Mansour

NeurIPS 2024 Fast Rates for Bandit PAC Multiclass Classification Liad Erez, Alon Cohen, Tomer Koren, Yishay Mansour, Shay Moran

AISTATS 2024 Faster Convergence with MultiWay Preferences Aadirupa Saha, Vitaly Feldman, Yishay Mansour, Tomer Koren

NeurIPS 2024 How to Boost Any Loss Function Richard Nock, Yishay Mansour

COLT 2024 Learnability Gaps of Strategic Classification Lee Cohen, Yishay Mansour, Shay Moran, Han Shao

NeurIPS 2024 Learning-Augmented Algorithms with Explicit Predictors Marek Eliáš, Haim Kaplan, Yishay Mansour, Shay Moran

ALT 2024 Partially Interpretable Models with Guarantees on Coverage and Accuracy Nave Frost, Zachary Lipton, Yishay Mansour, Michal Moshkovitz

AAAI 2024 Principal-Agent Reward Shaping in MDPs Omer Ben-Porat, Yishay Mansour, Michal Moshkovitz, Boaz Taitler

ICML 2024 Rate-Optimal Policy Optimization for Linear Markov Decision Processes Uri Sherman, Alon Cohen, Tomer Koren, Yishay Mansour

COLT 2024 The Real Price of Bandit Information in Multiclass Classification Liad Erez, Alon Cohen, Tomer Koren, Yishay Mansour, Shay Moran

NeurIPS 2023 Black-Box Differential Privacy for Interactive ML Haim Kaplan, Yishay Mansour, Shay Moran, Kobbi Nissim, Uri Stemmer

ICML 2023 Concurrent Shuffle Differential Privacy Under Continual Observation Jay Tenenbaum, Haim Kaplan, Yishay Mansour, Uri Stemmer

ICML 2023 Efficient Rate Optimal Regret for Adversarial Contextual MDPs Using Online Function Approximation Orin Levy, Alon Cohen, Asaf Cassel, Yishay Mansour

NeurIPS 2023 Eliciting User Preferences for Personalized Multi-Objective Decision Making Through Comparative Feedback Han Shao, Lee Cohen, Avrim Blum, Yishay Mansour, Aadirupa Saha, Matthew Walter

NeurIPS 2023 Finding Safe Zones of Markov Decision Processes Policies Lee Cohen, Yishay Mansour, Michal Moshkovitz

ICML 2023 Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation Uri Sherman, Tomer Koren, Yishay Mansour

AAAI 2023 Learning Revenue Maximization Using Posted Prices for Stochastic Strategic Patient Buyers Eitan-Hai Mashiah, Idan Attias, Yishay Mansour

NeurIPS 2023 Multiclass Boosting: Simple and Intuitive Weak Learning Criteria Nataly Brukhim, Amit Daniely, Yishay Mansour, Shay Moran

AAAI 2023 Optimism in Face of a Context: Regret Guarantees for Stochastic Contextual MDP Orin Levy, Yishay Mansour

ALT 2023 Pseudonorm Approachability and Applications to Regret Minimization Christoph Dann, Yishay Mansour, Mehryar Mohri, Jon Schneider, Balubramanian Sivan

ICML 2023 Random Classification Noise Does Not Defeat All Convex Potential Boosters Irrespective of Model Choice Yishay Mansour, Richard Nock, Robert Williamson

ICML 2023 Regret Minimization and Convergence to Equilibria in General-Sum Markov Games Liad Erez, Tal Lancewicki, Uri Sherman, Tomer Koren, Yishay Mansour

ICML 2023 Reinforcement Learning Can Be More Efficient with Multiple Rewards Christoph Dann, Yishay Mansour, Mehryar Mohri

NeurIPS 2022 A Characterization of Semi-Supervised Adversarially Robust PAC Learnability Idan Attias, Steve Hanneke, Yishay Mansour

NeurIPSW 2022 A Theory of Learning with Competing Objectives and User Feedback Pranjal Awasthi, Corinna Cortes, Yishay Mansour, Mehryar Mohri

NeurIPSW 2022 A Theory of Learning with Competing Objectives and User Feedback Pranjal Awasthi, Corinna Cortes, Yishay Mansour, Mehryar Mohri

NeurIPS 2022 Benign Underfitting of Stochastic Gradient Descent Tomer Koren, Roi Livni, Yishay Mansour, Uri Sherman

ICML 2022 Cooperative Online Learning in Stochastic and Adversarial MDPs Tal Lancewicki, Aviv Rosenberg, Yishay Mansour

NeurIPS 2022 Fair Wrapping for Black-Box Predictions Alexander Soen, Ibrahim M Alabdulmohsin, Sanmi Koyejo, Yishay Mansour, Nyalleng Moorosi, Richard Nock, Ke Sun, Lexing Xie

NeurIPSW 2022 Finding Safe Zones of Markov Decision Processes Policies Michal Moshkovitz, Lee Cohen, Yishay Mansour

ICML 2022 FriendlyCore: Practical Differentially Private Aggregation Eliad Tsfadia, Edith Cohen, Haim Kaplan, Yishay Mansour, Uri Stemmer

ICML 2022 Guarantees for Epsilon-Greedy Reinforcement Learning with Function Approximation Chris Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan

JMLR 2022 Improved Generalization Bounds for Adversarially Robust Learning Idan Attias, Aryeh Kontorovich, Yishay Mansour

AAAI 2022 Learning Adversarial Markov Decision Processes with Delayed Feedback Tal Lancewicki, Aviv Rosenberg, Yishay Mansour

AAAI 2022 Modeling Attrition in Recommender Systems with Departing Bandits Omer Ben-Porat, Lee Cohen, Liu Leqi, Zachary C. Lipton, Yishay Mansour

COLT 2022 Monotone Learning Olivier J Bousquet, Amit Daniely, Haim Kaplan, Yishay Mansour, Shay Moran, Uri Stemmer

NeurIPS 2022 Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback Tiancheng Jin, Tal Lancewicki, Haipeng Luo, Yishay Mansour, Aviv Rosenberg

JMLR 2022 Nonstochastic Bandits with Composite Anonymous Feedback Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, Claudio Gentile, Yishay Mansour

COLT 2022 Strategizing Against Learners in Bayesian Games Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan

AISTATS 2021 A Theory of Multiple-Source Adaptation with Limited Target Labeled Data Yishay Mansour, Mehryar Mohri, Jae Ro, Ananda Theertha Suresh, Ke Wu

ICML 2021 Adversarial Dueling Bandits Aadirupa Saha, Tomer Koren, Yishay Mansour

NeurIPS 2021 Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations Ayush Sekhari, Christoph Dann, Mehryar Mohri, Yishay Mansour, Karthik Sridharan

NeurIPS 2021 Differentially Private Multi-Armed Bandits in the Shuffle Model Jay Tenenbaum, Haim Kaplan, Yishay Mansour, Uri Stemmer

ICML 2021 Differentially-Private Clustering of Easy Instances Edith Cohen, Haim Kaplan, Yishay Mansour, Uri Stemmer, Eliad Tsfadia

NeurIPS 2021 Dueling Bandits with Team Comparisons Lee Cohen, Ulrike Schmidt-Kraepelin, Yishay Mansour

ICML 2021 Dueling Convex Optimization Aadirupa Saha, Tomer Koren, Yishay Mansour

NeurIPS 2021 Minimax Regret for Stochastic Shortest Path Alon Cohen, Yonathan Efroni, Yishay Mansour, Aviv Rosenberg

COLT 2021 Online Markov Decision Processes with Aggregate Bandit Feedback Alon Cohen, Haim Kaplan, Tomer Koren, Yishay Mansour

NeurIPS 2021 Optimal Rates for Random Order Online Optimization Uri Sherman, Tomer Koren, Yishay Mansour

NeurIPS 2021 Oracle-Efficient Regret Minimization in Factored MDPs with Unknown Structure Aviv Rosenberg, Yishay Mansour

NeurIPS 2021 ROI Maximization in Stochastic Online Decision-Making Nicolò Cesa-Bianchi, Tom Cesari, Yishay Mansour, Vianney Perchet

ICML 2021 Stochastic Multi-Armed Bandits with Unrestricted Delay Distributions Tal Lancewicki, Shahar Segal, Tomer Koren, Yishay Mansour

IJCAI 2021 Stochastic Shortest Path with Adversarially Changing Costs Aviv Rosenberg, Yishay Mansour

COLT 2021 The Sparse Vector Technique, Revisited Haim Kaplan, Yishay Mansour, Uri Stemmer

NeurIPS 2020 Adversarially Robust Streaming Algorithms via Differential Privacy Avinatan Hasidim, Haim Kaplan, Yishay Mansour, Yossi Matias, Uri Stemmer

AAAI 2020 Apprenticeship Learning via Frank-Wolfe Tom Zahavy, Alon Cohen, Haim Kaplan, Yishay Mansour

AAAI 2020 Designing Committees for Mitigating Biases Michal Feldman, Yishay Mansour, Noam Nisan, Sigal Oren, Moshe Tennenholtz

ICLR 2020 Detecting Malicious PDF Using CNN Raphael Fettaya, Yishay Mansour

ICML 2020 Near-Optimal Regret Bounds for Stochastic Shortest Path Aviv Rosenberg, Alon Cohen, Yishay Mansour, Haim Kaplan

IJCAI 2020 Online Revenue Maximization for Server Pricing Shant Boodaghians, Federico Fusco, Stefano Leonardi, Yishay Mansour, Ruta Mehta

ALT 2020 Planning in Hierarchical Reinforcement Learning: Guarantees for Using Local Policies Tom Zahavy, Avinatan Hasidim, Haim Kaplan, Yishay Mansour

NeurIPS 2020 Prediction with Corrupted Expert Advice Idan Amir, Idan Attias, Tomer Koren, Yishay Mansour, Roi Livni

NeurIPS 2020 Private Learning of Halfspaces: Simplifying the Construction and Reducing the Sample Complexity Haim Kaplan, Yishay Mansour, Uri Stemmer, Eliad Tsfadia

COLT 2020 Privately Learning Thresholds: Closing the Exponential Gap Haim Kaplan, Katrina Ligett, Yishay Mansour, Moni Naor, Uri Stemmer

NeurIPS 2020 Reinforcement Learning with Feedback Graphs Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan

NeurIPS 2020 Sample Complexity of Uniform Convergence for Multicalibration Eliran Shabat, Lee Cohen, Yishay Mansour

ALT 2020 Thompson Sampling for Adversarial Bit Prediction Yuval Lewi, Haim Kaplan, Yishay Mansour

ALT 2020 Top-$k$ Combinatorial Bandits with Full-Bandit Feedback Idan Rejwan, Yishay Mansour

UAI 2020 Unknown Mixing Times in Apprenticeship and Reinforcement Learning Tom Zahavy, Alon Cohen, Haim Kaplan, Yishay Mansour

ICML 2019 Adversarial Online Learning with Noise Alon Resler, Yishay Mansour

ALT 2019 Competitive Ratio vs Regret Minimization: Achieving the Best of Both Worlds Amit Daniely, Yishay Mansour

JMLR 2019 Delay and Cooperation in Nonstochastic Bandits Nicolò Cesa-Bianchi, Claudio Gentile, Yishay Mansour

ICML 2019 Differentially Private Learning of Geometric Concepts Haim Kaplan, Yishay Mansour, Yossi Matias, Uri Stemmer

NeurIPS 2019 Graph-Based Discriminators: Sample Complexity and Expressiveness Roi Livni, Yishay Mansour

ALT 2019 Improved Generalization Bounds for Robust Learning Idan Attias, Aryeh Kontorovich, Yishay Mansour

NeurIPS 2019 Individual Regret in Cooperative Nonstochastic Multi-Armed Bandits Yogev Bar-On, Yishay Mansour

ICML 2019 Learning Linear-Quadratic Regulators Efficiently with Only $\sqrt{T}$ Regret Alon Cohen, Tomer Koren, Yishay Mansour

NeurIPS 2019 Learning to Screen Alon Cohen, Avinatan Hassidim, Haim Kaplan, Yishay Mansour, Shay Moran

ICML 2019 Online Convex Optimization in Adversarial Markov Decision Processes Aviv Rosenberg, Yishay Mansour

NeurIPS 2019 Online Stochastic Shortest Path with Bandit Feedback and Unknown Transition Function Aviv Rosenberg, Yishay Mansour

AISTATS 2018 Discriminative Learning of Prediction Intervals Nir Rosenfeld, Yishay Mansour, Elad Yom-Tov

ALT 2018 Learning Decision Trees with Stochastic Linear Classifiers Tom Jurgenson, Yishay Mansour

COLT 2018 Nonstochastic Bandits with Composite Anonymous Feedback Nicolò Cesa-Bianchi, Claudio Gentile, Yishay Mansour

ICML 2018 Online Linear Quadratic Control Alon Cohen, Avinatan Hasidim, Tomer Koren, Nevena Lazic, Yishay Mansour, Kunal Talwar

IJCAI 2018 Planning and Learning with Stochastic Action Sets Craig Boutilier, Alon Cohen, Avinatan Hassidim, Yishay Mansour, Ofer Meshi, Martin Mladenov, Dale Schuurmans

ALT 2018 Robust Inference for Multiclass Classification Uriel Feige, Yishay Mansour, Robert E. Schapire

COLT 2017 Bandits with Movement Costs and Adaptive Pricing Tomer Koren, Roi Livni, Yishay Mansour

COLT 2017 Efficient Co-Training of Linear Separators Under Weak Dependence Avrim Blum, Yishay Mansour

COLT 2017 Efficient PAC Learning from the Crowd Pranjal Awasthi, Avrim Blum, Nika Haghtalab, Yishay Mansour

AAAI 2017 Label Efficient Learning by Exploiting Multi-Class Output Codes Maria-Florina Balcan, Travis Dick, Yishay Mansour

NeurIPS 2017 Multi-Armed Bandits with Metric Movement Costs Tomer Koren, Roi Livni, Yishay Mansour

NeurIPS 2017 Submultiplicative Glivenko-Cantelli and Uniform Convergence of Revenues Noga Alon, Moshe Babaioff, Yannai A. Gonczarowski, Yishay Mansour, Shay Moran, Amir Yehudayoff

COLT 2016 Delay and Cooperation in Nonstochastic Bandits Nicolò Cesa-Bianchi, Claudio Gentile, Yishay Mansour, Alberto Minora

MLJ 2016 Lower Bounds on Individual Sequence Regret Eyal Gofer, Yishay Mansour

COLT 2016 Online Learning with Low Rank Experts Elad Hazan, Tomer Koren, Roi Livni, Yishay Mansour

NeurIPS 2016 Online Pricing with Strategic and Patient Buyers Michal Feldman, Tomer Koren, Roi Livni, Yishay Mansour, Aviv Zohar

ICML 2015 Classification with Low Rank and Missing Data Elad Hazan, Roi Livni, Yishay Mansour

AAAI 2015 Learning Valuation Distributions from Partial Observation Avrim Blum, Yishay Mansour, Jamie Morgenstern

COLT 2015 Learning and Inference in the Presence of Corrupted Inputs Uriel Feige, Yishay Mansour, Robert E. Schapire

COLT 2015 On the Complexity of Learning with Kernels Nicolò Cesa-Bianchi, Yishay Mansour, Ohad Shamir

ICML 2014 Thompson Sampling for Complex Online Problems Aditya Gopalan, Shie Mannor, Yishay Mansour

ICML 2013 Exploiting Ontology Structures and Unlabeled Data for Learning Nina Balcan, Avrim Blum, Yishay Mansour

NeurIPS 2013 From Bandits to Experts: A Tale of Domination and Independence Noga Alon, Nicolò Cesa-Bianchi, Claudio Gentile, Yishay Mansour

COLT 2013 Regret Minimization for Branching Experts Eyal Gofer, Nicolò Cesa-Bianchi, Claudio Gentile, Yishay Mansour

COLT 2012 Distributed Learning, Communication Complexity and Privacy Maria Florina Balcan, Avrim Blum, Shai Fine, Yishay Mansour

NeurIPS 2012 Learning Multiple Tasks Using Shared Hypotheses Koby Crammer, Yishay Mansour

ALT 2012 Lower Bounds on Individual Sequence Regret Eyal Gofer, Yishay Mansour

ALT 2011 Regret Minimization Algorithms for Pricing Lookback Options Eyal Gofer, Yishay Mansour

NeurIPS 2010 Learning Bounds for Importance Weighting Corinna Cortes, Yishay Mansour, Mehryar Mohri

COLT 2010 Learning with Global Cost in Stochastic Environments Eyal Even-Dar, Shie Mannor, Yishay Mansour

COLT 2010 Regret Minimization with Concept Drift Koby Crammer, Yishay Mansour, Eyal Even-Dar, Jennifer Wortman Vaughan

COLT 2009 Domain Adaptation: Learning Bounds and Algorithms Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh

ALT 2009 Learning and Domain Adaptation Yishay Mansour

UAI 2009 Multiple Source Adaptation and the Rényi Divergence Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh

COLT 2009 Online Learning for Global Cost Functions Eyal Even-Dar, Robert Kleinberg, Shie Mannor, Yishay Mansour

COLT 2009 Reliable Agnostic Learning Adam Tauman Kalai, Varun Kanade, Yishay Mansour

NeurIPS 2008 Domain Adaptation with Multiple Sources Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh

MLJ 2008 Regret to the Best vs. Regret to the Average Eyal Even-Dar, Michael J. Kearns, Yishay Mansour, Jennifer Wortman

MLJ 2007 Active Sampling for Multiple Output Identification Shai Fine, Yishay Mansour

JMLR 2007 From External to Internal Regret Avrim Blum, Yishay Mansour

MLJ 2007 Improved Second-Order Bounds for Prediction with Expert Advice Nicolò Cesa-Bianchi, Yishay Mansour, Gilles Stoltz

COLT 2007 Regret to the Best vs. Regret to the Average Eyal Even-Dar, Michael J. Kearns, Yishay Mansour, Jennifer Wortman

IJCAI 2007 The Value of Observation for Monitoring Dynamic Systems Eyal Even-Dar, Sham M. Kakade, Yishay Mansour

JMLR 2006 Action Elimination and Stopping Conditions for the Multi-Armed Bandit and Reinforcement Learning Problems Eyal Even-Dar, Shie Mannor, Yishay Mansour

COLT 2006 Active Sampling for Multiple Output Identification Shai Fine, Yishay Mansour

JMLR 2005 Concentration Bounds for Unigram Language Models Evgeny Drukh, Yishay Mansour

COLT 2005 From External to Internal Regret Avrim Blum, Yishay Mansour

COLT 2005 Improved Second-Order Bounds for Prediction with Expert Advice Nicolò Cesa-Bianchi, Yishay Mansour, Gilles Stoltz

UAI 2005 Planning in POMDPs Using Multiplicity Automata Eyal Even-Dar, Sham M. Kakade, Yishay Mansour

IJCAI 2005 Reinforcement Learning in POMDPs Without Resets Eyal Even-Dar, Sham M. Kakade, Yishay Mansour

COLT 2004 Concentration Bounds for Unigrams Language Model Evgeny Drukh, Yishay Mansour

NeurIPS 2004 Experts in a Markov Decision Process Eyal Even-dar, Sham M. Kakade, Yishay Mansour

ICML 2003 Action Elimination and Stopping Conditions for Reinforcement Learning Eyal Even-Dar, Shie Mannor, Yishay Mansour

COLT 2003 Approximate Equivalence of Markov Decision Processes Eyal Even-Dar, Yishay Mansour

JMLR 2003 Learning Rates for Q-Learning Eyal Even Dar, Yishay Mansour

MLJ 2002 A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes Michael J. Kearns, Yishay Mansour, Andrew Y. Ng

UAI 2002 Efficient Nash Computation in Large Population Games with Bounded Influence Michael J. Kearns, Yishay Mansour

COLT 2002 PAC Bounds for Multi-Armed Bandit and Markov Decision Processes Eyal Even-Dar, Shie Mannor, Yishay Mansour

COLT 2001 Agnostic Boosting Shai Ben-David, Philip M. Long, Yishay Mansour

NeurIPS 2001 Convergence of Optimistic and Incremental Q-Learning Eyal Even-dar, Yishay Mansour

COLT 2001 Learning Rates for Q-Learning Eyal Even-Dar, Yishay Mansour

MLJ 2001 Learning with Maximum-Entropy Distributions Yishay Mansour, Mariano Schain

AISTATS 2001 Why Averaging Classifiers Can Protect Against Overfitting Yoav Freund, Yishay Mansour, Robert E. Schapire

COLT 2000 Boosting Using Branching Programs Yishay Mansour, David A. McAllester

UAI 2000 Fast Planning in Stochastic Games Michael J. Kearns, Yishay Mansour, Satinder Singh

COLT 2000 Generalization Bounds for Decision Trees Yishay Mansour, David A. McAllester

MLJ 2000 Implementation Issues in the Fourier Transform Algorithm Yishay Mansour, Sigal Sahar

UAI 2000 Nash Convergence of Gradient Dynamics in General-Sum Games Satinder Singh, Michael J. Kearns, Yishay Mansour

IJCAI 1999 A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes Michael J. Kearns, Yishay Mansour, Andrew Y. Ng

NeurIPS 1999 Approximate Planning in Large POMDPs via Reusable Trajectories Michael J. Kearns, Yishay Mansour, Andrew Y. Ng

NeurIPS 1999 Boosting with Multi-Way Branching in Decision Trees Yishay Mansour, David A. McAllester

COLT 1999 Estimating a Mixture of Two Product Distributions Yoav Freund, Yishay Mansour

UAI 1999 On the Complexity of Policy Iteration Yishay Mansour, Satinder Singh

NeurIPS 1999 Policy Gradient Methods for Reinforcement Learning with Function Approximation Richard S. Sutton, David A. McAllester, Satinder P. Singh, Yishay Mansour

COLT 1999 Reinforcement Learning and Mistake Bounded Algorithms Yishay Mansour

ICML 1998 A Fast, Bottom-up Decision Tree Pruning Algorithm with Near-Optimal Generalization Michael J. Kearns, Yishay Mansour

UAI 1998 Exact Inference of Hidden Structure from Sample Data in Noisy-or Networks Michael J. Kearns, Yishay Mansour

COLT 1998 Proceedings of the Eleventh Annual Conference on Computational Learning Theory, COLT 1998, Madison, Wisconsin, USA, July 24-26, 1998 Peter L. Bartlett, Yishay Mansour

MLJ 1997 An Experimental and Theoretical Comparison of Model Selection Methods Michael J. Kearns, Yishay Mansour, Andrew Y. Ng, Dana Ron

UAI 1997 An Information-Theoretic Analysis of Hard and Soft Assignment Methods for Clustering Michael J. Kearns, Yishay Mansour, Andrew Y. Ng

COLT 1997 Learning with Maximum-Entropy Distributions Yishay Mansour, Mariano Schain

MLJ 1997 Online Learning Versus Offline Learning Shai Ben-David, Eyal Kushilevitz, Yishay Mansour

ICML 1997 Pessimistic Decision Tree Pruning Based Continuous-Time Yishay Mansour

ICML 1996 Applying the Waek Learning Framework to Understand and Improve C4.5 Thomas G. Dietterich, Michael J. Kearns, Yishay Mansour

COLT 1995 An Experimental and Theoretical Comparison of Model Selection Methods Michael J. Kearns, Yishay Mansour, Andrew Y. Ng, Dana Ron

NeurIPS 1995 Implementation Issues in the Fourier Transform Algorithm Yishay Mansour, Sigal Sahar

COLT 1992 An O(nlog Log N) Learning Algorithm for DNF Under the Uniform Distribution Yishay Mansour

COLT 1991 Learning Monotone Kµ DNF Formulas on Product Distributions Thomas R. Hancock, Yishay Mansour

COLT 1989 A Parametrization Scheme for Classifying Models of Learnability Shai Ben-David, Gyora M. Benedek, Yishay Mansour

COLT 1988 Results on Learnability and the Vapnick-Chervonenkis Dimension Nathan Linial, Yishay Mansour, Ronald L. Rivest