Mannor, Shie

228 publications

ICML 2025 A Classification View on Meta Learning Bandits Mirco Mutti, Jeongyeol Kwon, Shie Mannor, Aviv Tamar

NeurIPS 2025 Efficient Fairness-Performance Pareto Front Computation Mark Kozdoba, Binyamin Perets, Shie Mannor

ICLRW 2025 From Medical Literature to Predictive Features: An Evidence-Based Knowledge Graph Approach Donghee Choi, Antoine D Lain, Joram M. Posma, Mark Kozdoba, Binyamin Perets, Shie Mannor

ICLR 2025 Global Convergence of Policy Gradient in Average Reward MDPs Navdeep Kumar, Yashaswini Murthy, Itai Shufaro, Kfir Yehuda Levy, R. Srikant, Shie Mannor

ICLRW 2025 GluFormer: Learning Generalizable Representations from Continuous Glucose Monitoring Data Guy Lutsker, Gal Sapir, Smadar Shilo, Jordi Merino, Anastasia Godneva, Jerry R Greenfield, Dorit Samocha-Bonet, Raja Dhir, Francisco Gude, Shie Mannor, Eli Meirom, Gal Chechik, Hagai Rossman, Eran Segal

NeurIPS 2025 Non-Rectangular Robust MDPs with Normed Uncertainty Sets Navdeep Kumar, Adarsh Gupta, Maxence Mohamed Elfatihi, Giorgia Ramponi, Kfir Yehuda Levy, Shie Mannor

ICLR 2025 On Bits and Bandits: Quantifying the Regret-Information Trade-Off Itai Shufaro, Nadav Merlis, Nir Weinberger, Shie Mannor

NeurIPS 2025 On the Convergence of Single-Timescale Actor-Critic Navdeep Kumar, Priyank Agrawal, Giorgia Ramponi, Kfir Yehuda Levy, Shie Mannor

ICML 2025 Policy Gradient with Tree Expansion Gal Dalal, Assaf Hallak, Gugan Thoppe, Shie Mannor, Gal Chechik

NeurIPS 2025 Policy Optimized Text-to-Image Pipeline Design Uri Gadot, Rinon Gal, Yftah Ziser, Gal Chechik, Shie Mannor

CVPR 2025 RL-RC-DoT: A Block-Level RL Agent for Task-Aware Video Compression Uri Gadot, Assaf Shocher, Shie Mannor, Gal Chechik, Assaf Hallak

ICML 2025 Reinforcement Learning with Segment Feedback Yihan Du, Anna Winnicki, Gal Dalal, Shie Mannor, R. Srikant

NeurIPS 2025 State Entropy Regularization for Robust Reinforcement Learning Yonatan Ashlag, Uri Koren, Mirco Mutti, Esther Derman, Pierre-Luc Bacon, Shie Mannor

ICML 2024 Bring Your Own (Non-Robust) Algorithm to Solve Robust MDPs by Estimating the Worst Kernel Uri Gadot, Kaixin Wang, Navdeep Kumar, Kfir Yehuda Levy, Shie Mannor

ICML 2024 Efficient Value Iteration for S-Rectangular Robust Markov Decision Processes Navdeep Kumar, Kaixin Wang, Kfir Yehuda Levy, Shie Mannor

ICML 2024 Exploration-Driven Policy Optimization in RLHF: Theoretical Insights on Efficient Data Utilization Yihan Du, Anna Winnicki, Gal Dalal, Shie Mannor, R. Srikant

ICML 2024 Improving Token-Based World Models with Parallel Observation Prediction Lior Cohen, Kaixin Wang, Bingyi Kang, Shie Mannor

ECCVW 2024 PlaMo: Plan and Move in Rich 3D Physical Environments Assaf Hallak, Gal Dalal, Chen Tessler, Kelly Guo, Shie Mannor, Gal Chechik

ICML 2024 Prospective Side Information for Latent MDPs Jeongyeol Kwon, Yonathan Efroni, Shie Mannor, Constantine Caramanis

NeurIPS 2024 RL in Latent MDPs Is Tractable: Online Guarantees via Off-Policy Evaluation Jeongyeol Kwon, Shie Mannor, Constantine Caramanis, Yonathan Efroni

ICML 2024 Sobolev Space Regularised Pre Density Models Mark Kozdoba, Binyamin Perets, Shie Mannor

AAAI 2024 Solving Non-Rectangular Reward-Robust MDPs via Frequency Regularization Uri Gadot, Esther Derman, Navdeep Kumar, Maxence Mohamed Elfatihi, Kfir Levy, Shie Mannor

ICLR 2024 Tree Search-Based Policy Optimization Under Stochastic Execution Delay David Valensi, Esther Derman, Shie Mannor, Gal Dalal

NeurIPS 2023 Individualized Dosing Dynamics via Neural Eigen Decomposition Stav Belogolovsky, Ido Greenberg, Danny Eytan, Shie Mannor

NeurIPSW 2023 Individualized Dosing Dynamics via Neural Eigen Decomposition Stav Belogolovsky, Ido Greenberg, Danny Eytan, Shie Mannor

ICML 2023 Learning Hidden Markov Models When the Locations of Missing Observations Are Unknown Binyamin Perets, Mark Kozdoba, Shie Mannor

ICML 2023 Learning to Initiate and Reason in Event-Driven Cascading Processes Yuval Atzmon, Eli Meirom, Shie Mannor, Gal Chechik

ICLRW 2023 Learning to Initiate and Reason in Event-Driven Cascading Processes Yuval Atzmon, Eli Meirom, Shie Mannor, Gal Chechik

NeurIPS 2023 Optimization or Architecture: How to Hack Kalman Filtering Ido Greenberg, Netanel Yannay, Shie Mannor

ICMLW 2023 Optimization or Architecture: What Matters in Non-Linear Filtering? Ido Greenberg, Netanel Yannay, Shie Mannor

ICML 2023 PPG Reloaded: An Empirical Study on What Matters in Phasic Policy Gradient Kaixin Wang, Daquan Zhou, Jiashi Feng, Shie Mannor

AAAI 2023 Planning and Learning with Adaptive Lookahead Aviv Rosenberg, Assaf Hallak, Shie Mannor, Gal Chechik, Gal Dalal

NeurIPS 2023 Policy Gradient for Rectangular Robust Markov Decision Processes Navdeep Kumar, Esther Derman, Matthieu Geist, Kfir Y. Levy, Shie Mannor

ICML 2023 Representation-Driven Reinforcement Learning Ofir Nabati, Guy Tennenholtz, Shie Mannor

ICML 2023 Reward-Mixing MDPs with Few Latent Contexts Are Learnable Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor

NeurIPSW 2023 Robustness and Regularization in Reinforcement Learning Esther Derman, Yevgeniy Men, Matthieu Geist, Shie Mannor

NeurIPSW 2023 Targeted Uncertainty Reduction in Robust MDPs Uri Gadot, Kaixin Wang, Esther Derman, Navdeep Kumar, Kfir Levy, Shie Mannor

NeurIPS 2023 Train Hard, Fight Easy: Robust Meta Reinforcement Learning Ido Greenberg, Shie Mannor, Gal Chechik, Eli Meirom

NeurIPSW 2023 Unnormalized Density Estimation with Root Sobolev Norm Regularization Mark Kozdoba, Binyamin Perets, Shie Mannor

ICML 2022 Actor-Critic Based Improper Reinforcement Learning Mohammadi Zaki, Avi Mohan, Aditya Gopalan, Shie Mannor

ICML 2022 Analysis of Stochastic Processes Through Replay Buffers Shirli Di-Castro, Shie Mannor, Dotan Di Castro

ICML 2022 Coordinated Attacks Against Contextual Bandits: Fundamental Limits and Defense Mechanisms Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor

CoRL 2022 DiffStack: A Differentiable and Modular Control Stack for Autonomous Vehicles Peter Karkus, Boris Ivanovic, Shie Mannor, Marco Pavone

NeurIPS 2022 Efficient Risk-Averse Reinforcement Learning Ido Greenberg, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor

NeurIPS 2022 Finite Sample Analysis of Dynamic Regression Parameter Learning Mark Kozdoba, Edward Moroshko, Shie Mannor, Yacov Crammer

ICLRW 2022 Learning to Reason About and to Act on Physical Cascading Events Yuval Atzmon, Eli Meirom, Shie Mannor, Gal Chechik

AAAI 2022 Locality Matters: A Scalable Value Decomposition Approach for Cooperative Multi-Agent Reinforcement Learning Roy Zohar, Shie Mannor, Guy Tennenholtz

ICLR 2022 On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning Guy Tennenholtz, Assaf Hallak, Gal Dalal, Shie Mannor, Gal Chechik, Uri Shalit

AAAI 2022 Online Apprenticeship Learning Lior Shani, Tom Zahavy, Shie Mannor

ICML 2022 Optimizing Tensor Network Contraction Using Reinforcement Learning Eli Meirom, Haggai Maron, Shie Mannor, Gal Chechik

AAAI 2022 Reinforcement Learning for Datacenter Congestion Control Chen Tessler, Yuval Shpigelman, Gal Dalal, Amit Mandelbaum, Doron Haritan Kazakov, Benjamin Fuhrer, Gal Chechik, Shie Mannor

NeurIPS 2022 Reinforcement Learning with a Terminator Guy Tennenholtz, Nadav Merlis, Lior Shani, Shie Mannor, Uri Shalit, Gal Chechik, Assaf Hallak, Gal Dalal

NeurIPSW 2022 SoftTreeMax: Policy Gradient with Tree Search Gal Dalal, Assaf Hallak, Shie Mannor, Gal Chechik

ICML 2022 The Geometry of Robust Value Functions Kaixin Wang, Navdeep Kumar, Kuangqi Zhou, Bryan Hooi, Jiashi Feng, Shie Mannor

NeurIPS 2022 Tractable Optimality in Episodic Latent MABs Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor

NeurIPS 2022 Uncertainty Estimation Using Riemannian Model Dynamics for Offline Reinforcement Learning Guy Tennenholtz, Shie Mannor

ICLR 2021 Acting in Delayed Environments with Non-Stationary Markov Policies Esther Derman, Gal Dalal, Shie Mannor

UAI 2021 Action Redundancy in Reinforcement Learning Nir Baram, Guy Tennenholtz, Shie Mannor

UAI 2021 Bandits with Partially Observable Confounded Data Guy Tennenholtz, Uri Shalit, Shie Mannor, Yonathan Efroni

ICML 2021 Confidence-Budget Matching for Sequential Budgeted Learning Yonathan Efroni, Nadav Merlis, Aadirupa Saha, Shie Mannor

ICML 2021 Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks Eli Meirom, Haggai Maron, Shie Mannor, Gal Chechik

NeurIPSW 2021 Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning Guy Tennenholtz, Assaf Hallak, Gal Dalal, Shie Mannor, Gal Chechik, Uri Shalit

ICML 2021 Detecting Rewards Deterioration in Episodic Reinforcement Learning Ido Greenberg, Shie Mannor

NeurIPS 2021 Improve Agents Without Retraining: Parallel Tree Search with Off-Policy Correction Gal Dalal, Assaf Hallak, Steven Dalton, Iuri Frosio, Shie Mannor, Gal Chechik

MLJ 2021 Inverse Reinforcement Learning in Contextual MDPs Stav Belogolovsky, Philip Korsunsky, Shie Mannor, Chen Tessler, Tom Zahavy

UAI 2021 Known Unknowns: Learning Novel Concepts Using Reasoning-by-Elimination Harsh Agrawal, Eli A. Meirom, Yuval Atzmon, Shie Mannor, Gal Chechik

NeurIPSW 2021 Latent Geodesics of Model Dynamics for Offline Reinforcement Learning Guy Tennenholtz, Nir Baram, Shie Mannor

AAAI 2021 Lenient Regret for Multi-Armed Bandits Nadav Merlis, Shie Mannor

ICML 2021 Online Limited Memory Neural-Linear Bandits with Likelihood Matching Ofir Nabati, Tom Zahavy, Shie Mannor

ICLR 2021 Optimizing Memory Placement Using Evolutionary Graph Reinforcement Learning Shauharda Khadka, Estelle Aflalo, Mattias Marder, Avrech Ben-David, Santiago Miret, Shie Mannor, Tamir Hazan, Hanlin Tang, Somdeb Majumdar

CVPR 2021 Over-the-Air Adversarial Flickering Attacks Against Video Recognition Networks Roi Pony, Itay Naeh, Shie Mannor

NeurIPS 2021 RL for Latent MDPs: Regret Guarantees and a Lower Bound Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor

NeurIPS 2021 Reinforcement Learning in Reward-Mixing MDPs Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor

AAAI 2021 Reinforcement Learning with Trajectory Feedback Yonathan Efroni, Nadav Merlis, Shie Mannor

NeurIPS 2021 Sim and Real: Better Together Shirli Di-Castro, Dotan Di Castro, Shie Mannor

NeurIPS 2021 Twice Regularized MDPs and the Equivalence Between Robustness and Regularization Esther Derman, Matthieu Geist, Shie Mannor

ICML 2021 Value Iteration in Continuous Actions, States and Time Michael Lutter, Shie Mannor, Jan Peters, Dieter Fox, Animesh Garg

AAAI 2020 Adaptive Trust Region Policy Optimization: Global Convergence and Faster Rates for Regularized MDPs Lior Shani, Yonathan Efroni, Shie Mannor

ALT 2020 An Adaptive Stochastic Optimization Algorithm for Resource Allocation Xavier Fontaine, Shie Mannor, Vianney Perchet

AAAI 2020 Off-Policy Evaluation in Partially Observable Environments Guy Tennenholtz, Uri Shalit, Shie Mannor

NeurIPS 2020 Online Planning with Lookahead Policies Yonathan Efroni, Mohammad Ghavamzadeh, Shie Mannor

ICML 2020 Optimistic Policy Optimization with Bandit Feedback Lior Shani, Yonathan Efroni, Aviv Rosenberg, Shie Mannor

WACV 2020 Scalable Detection of Offensive and Non-Compliant Content / Logo in Product Images Shreyansh Gandhi, Samrat Kokkula, Abon Chaudhuri, Alessandro Magnani, Theban Stanley, Behzad Ahmadi, Venkatesh Kandaswamy, Omer Ovenc, Shie Mannor

COLT 2020 Tight Lower Bounds for Combinatorial Multi-Armed Bandits Nadav Merlis, Shie Mannor

ICML 2020 Topic Modeling via Full Dependence Mixtures Dan Fisher, Mark Kozdoba, Shie Mannor

UAI 2019 A Bayesian Approach to Robust Reinforcement Learning Esther Derman, Daniel Mankowitz, Timothy Mann, Shie Mannor

ICML 2019 Action Robust Reinforcement Learning and Applications in Continuous Control Chen Tessler, Yonathan Efroni, Shie Mannor

COLT 2019 Batch-Size Independent Regret Bounds for the Combinatorial Multi-Armed Bandit Problem Nadav Merlis, Shie Mannor

NeurIPS 2019 Distributional Policy Optimization: An Alternative Approach for Continuous Control Chen Tessler, Guy Tennenholtz, Shie Mannor

ICML 2019 Exploration Conscious Reinforcement Learning Revisited Lior Shani, Yonathan Efroni, Shie Mannor

AAAI 2019 How to Combine Tree-Search Methods in Reinforcement Learning Yonathan Efroni, Gal Dalal, Bruno Scherrer, Shie Mannor

ICML 2019 Nonlinear Distributional Gradient Temporal-Difference Learning Chao Qu, Shie Mannor, Huan Xu

AAAI 2019 On-Line Learning of Linear Dynamical Systems: Exponential Forgetting in Kalman Filters Mark Kozdoba, Jakub Marecek, Tigran T. Tchrakian, Shie Mannor

ICLR 2019 Reward Constrained Policy Optimization Chen Tessler, Daniel J. Mankowitz, Shie Mannor

ICML 2019 The Natural Language of Actions Guy Tennenholtz, Shie Mannor

NeurIPS 2019 Tight Regret Bounds for Model-Based Reinforcement Learning with Greedy Policies Yonathan Efroni, Nadav Merlis, Mohammad Ghavamzadeh, Shie Mannor

NeurIPS 2019 Value Propagation for Decentralized Networked Deep Multi-Agent Reinforcement Learning Chao Qu, Shie Mannor, Huan Xu, Yuan Qi, Le Song, Junwu Xiong

COLT 2018 A General Approach to Multi-Armed Bandits Under Risk Criteria Asaf B. Cassel, Shie Mannor, Assaf Zeevi

ICML 2018 Beyond the One-Step Greedy Approach in Reinforcement Learning Yonathan Efroni, Gal Dalal, Bruno Scherrer, Shie Mannor

AAAI 2018 Finite Sample Analyses for TD(0) with Function Approximation Gal Dalal, Balázs Szörényi, Gugan Thoppe, Shie Mannor

COLT 2018 Finite Sample Analysis of Two-Timescale Stochastic Approximation with Applications to Reinforcement Learning Gal Dalal, Gugan Thoppe, Balázs Szörényi, Shie Mannor

AAAI 2018 Is a Picture Worth a Thousand Words? a Deep Multi-Modal Architecture for Product Classification in E-Commerce Tom Zahavy, Abhinandan Krishnan, Alessandro Magnani, Shie Mannor

NeurIPS 2018 Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning Tom Zahavy, Matan Haroush, Nadav Merlis, Daniel J Mankowitz, Shie Mannor

AAAI 2018 Learning Robust Options Daniel J. Mankowitz, Timothy A. Mann, Pierre-Luc Bacon, Doina Precup, Shie Mannor

NeurIPS 2018 Multiple-Step Greedy Policies in Approximate and Online Reinforcement Learning Yonathan Efroni, Gal Dalal, Bruno Scherrer, Shie Mannor

UAI 2018 Soft-Robust Actor-Critic Policy-Gradient Esther Derman, Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor

AAAI 2017 A Deep Hierarchical Approach to Lifelong Learning in Minecraft Chen Tessler, Shahar Givony, Tom Zahavy, Daniel J. Mankowitz, Shie Mannor

IJCAI 2017 Approximate Value Iteration with Temporally Extended Actions (Extended Abstract) Timothy A. Mann, Shie Mannor, Doina Precup

ICML 2017 Consistent On-Line Off-Policy Evaluation Assaf Hallak, Shie Mannor

ICML 2017 End-to-End Differentiable Adversarial Imitation Learning Nir Baram, Oron Anschel, Itai Caspi, Shie Mannor

COLT 2017 Ignoring Is a Bliss: Learning with Large Noise Through Reweighting-Minimization Daniel Vainsencher, Shie Mannor, Huan Xu

ICML 2017 Multi-Objective Bandits: Optimizing the Generalized Gini Index Róbert Busa-Fekete, Balázs Szörényi, Paul Weng, Shie Mannor

ECML-PKDD 2017 Non-Parametric Online AUC Maximization Balázs Szörényi, Snir Cohen, Shie Mannor

NeurIPS 2017 Rotting Bandits Nir Levine, Koby Crammer, Shie Mannor

NeurIPS 2017 Shallow Updates for Deep Reinforcement Learning Nir Levine, Tom Zahavy, Daniel J Mankowitz, Aviv Tamar, Shie Mannor

NeurIPS 2016 Adaptive Skills Adaptive Partitions (ASAP) Daniel J Mankowitz, Timothy A Mann, Shie Mannor

AAAI 2016 Generalized Emphatic Temporal Difference Learning: Bias-Variance Analysis Assaf Hallak, Aviv Tamar, Rémi Munos, Shie Mannor

ICML 2016 Graying the Black Box: Understanding DQNs Tom Zahavy, Nir Ben-Zrihem, Shie Mannor

ICML 2016 Heteroscedastic Sequences: Beyond Gaussianity Oren Anava, Shie Mannor

ICML 2016 Hierarchical Decision Making in Electricity Grid Management Gal Dalal, Elad Gilboa, Shie Mannor

ECML-PKDD 2016 INSIGHT: Dynamic Traffic Management Using Heterogeneous Urban Data Nikolaos Panagiotou, Nikolas Zygouras, Ioannis Katakis, Dimitrios Gunopulos, Nikos Zacheilas, Ioannis Boutsis, Vana Kalogeraki, Stephen Lynch, Brendan O'Brien, Dermot Kinane, Jakub Marecek, Jia Yuan Yu, Rudi Verago, Elizabeth Daly, Nico Piatkowski, Thomas Liebig, Christian Bockermann, Katharina Morik, François Schnitzler, Matthias Weidlich, Avigdor Gal, Shie Mannor, Hendrik Stange, Werner Halft, Gennady L. Andrienko

JMLR 2016 Learning the Variance of the Reward-to-Go Aviv Tamar, Dotan Di Castro, Shie Mannor

JMLR 2016 Regularized Policy Iteration with Nonparametric Function Spaces Amir-massoud Farahmand, Mohammad Ghavamzadeh, Csaba Szepesvári, Shie Mannor

JAIR 2015 Approximate Value Iteration with Temporally Extended Actions Timothy A. Mann, Shie Mannor, Doina Precup

FnTML 2015 Bayesian Reinforcement Learning: A Survey Mohammad Ghavamzadeh, Shie Mannor, Joelle Pineau, Aviv Tamar

NeurIPS 2015 Community Detection via Measure Space Embedding Mark Kozdoba, Shie Mannor

ICML 2015 Dynamic Sensing: Better Classification Under Acquisition Constraints Oran Richman, Shie Mannor

ICML 2015 Off-Policy Model-Based Learning Under Unknown Factored Dynamics Assaf Hallak, Francois Schnitzler, Timothy Mann, Shie Mannor

NeurIPS 2015 Online Learning for Adversaries with Memory: Price of past Mistakes Oren Anava, Elad Hazan, Shie Mannor

AAAI 2015 Optimizing the CVaR via Sampling Aviv Tamar, Yonatan Glassner, Shie Mannor

NeurIPS 2015 Policy Gradient for Coherent Risk Measures Aviv Tamar, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor

NeurIPS 2015 Risk-Sensitive and Robust Decision-Making: A CVaR Optimization Approach Yinlam Chow, Aviv Tamar, Shie Mannor, Marco Pavone

AISTATS 2015 Sensor Selection for Crowdsensing Dynamical Systems François Schnitzler, Jia Yuan Yu, Shie Mannor

COLT 2015 Thompson Sampling for Learning Parameterized Markov Decision Processes Aditya Gopalan, Shie Mannor

COLT 2014 Approachability in Unknown Games: Online Learning Meets Multi-Objective Optimization Shie Mannor, Vianney Perchet, Gilles Stoltz

ICML 2014 Concept Drift Detection Through Resampling Maayan Harel, Shie Mannor, Ran El-Yaniv, Koby Crammer

ECML-PKDD 2014 Concurrent Bandits and Cognitive Radio Networks Orly Avner, Shie Mannor

ECML-PKDD 2014 Heterogeneous Stream Processing and Crowdsourcing for Traffic Monitoring: Highlights François Schnitzler, Alexander Artikis, Matthias Weidlich, Ioannis Boutsis, Thomas Liebig, Nico Piatkowski, Christian Bockermann, Katharina Morik, Vana Kalogeraki, Jakub Marecek, Avigdor Gal, Shie Mannor, Dermot Kinane, Dimitrios Gunopulos

NeurIPS 2014 How Hard Is My MDP?" the Distribution-Norm to the Rescue" Odalric-Ambrym Maillard, Timothy A Mann, Shie Mannor

ICML 2014 Latent Bandits. Odalric-Ambrym Maillard, Shie Mannor

NeurIPS 2014 Robust Logistic Regression and Classification Jiashi Feng, Huan Xu, Shie Mannor, Shuicheng Yan

ICML 2014 Scaling up Approximate Value Iteration with Options: Better Policies with Fewer Iterations Timothy Mann, Shie Mannor

ICML 2014 Scaling up Robust MDPs Using Function Approximation Aviv Tamar, Shie Mannor, Huan Xu

JMLR 2014 Set-Valued Approachability and Online Learning with Partial Monitoring Shie Mannor, Vianney Perchet, Gilles Stoltz

ECML-PKDD 2014 Sub-Sampling for Multi-Armed Bandits Akram Baransi, Odalric-Ambrym Maillard, Shie Mannor

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

ICML 2014 Time-Regularized Interrupting Options (TRIO) Timothy Mann, Daniel Mankowitz, Shie Mannor

COLT 2013 Approachability, Fast and Slow Vianney Perchet, Shie Mannor

NeurIPS 2013 Learning Multiple Models via Regularized Weighting Daniel Vainsencher, Shie Mannor, Huan Xu

COLT 2013 Online Learning for Time Series Prediction Oren Anava, Elad Hazan, Shie Mannor, Ohad Shamir

NeurIPS 2013 Online PCA for Contaminated Data Jiashi Feng, Huan Xu, Shie Mannor, Shuicheng Yan

COLT 2013 Opportunistic Strategies for Generalized No-Regret Problems Andrey Bernstein, Shie Mannor, Nahum Shimkin

NeurIPS 2013 Reinforcement Learning in Robust Markov Decision Processes Shiau Hong Lim, Huan Xu, Shie Mannor

ICML 2013 Robust Sparse Regression Under Adversarial Corruption Yudong Chen, Constantine Caramanis, Shie Mannor

ICML 2013 Temporal Difference Methods for the Variance of the Reward to Go Aviv Tamar, Dotan Di Castro, Shie Mannor

ICML 2012 Decoupling Exploration and Exploitation in Multi-Armed Bandits Orly Avner, Shie Mannor, Ohad Shamir

ICML 2012 Lightning Does Not Strike Twice: Robust MDPs with Coupled Uncertainty Shie Mannor, Ofir Mebel, Huan Xu

ACML 2012 More Is Better: Large Scale Partially-Supervised Sentiment Classification Yoav Haimovitch, Koby Crammer, Shie Mannor

ICML 2012 Policy Gradients with Variance Related Risk Criteria Dotan Di Castro, Aviv Tamar, Shie Mannor

COLT 2012 Preface Shie Mannor, Nathan Srebro, Robert C. Williamson

MLJ 2012 Robustness and Generalization Huan Xu, Shie Mannor

AISTATS 2012 Statistical Optimization in High Dimensions Huan Xu, Constantine Caramanis, Shie Mannor

NeurIPS 2012 The Perturbed Variation Maayan Harel, Shie Mannor

ECML-PKDD 2011 Activity Recognition with Mobile Phones Jordan Frank, Shie Mannor, Doina Precup

ICML 2011 Bundle Selling by Online Estimation of Valuation Functions Daniel Vainsencher, Ofer Dekel, Shie Mannor

NeurIPS 2011 Committing Bandits Loc X. Bui, Ramesh Johari, Shie Mannor

COLT 2011 Does an Efficient Calibrated Forecasting Strategy Exist? Jacob Abernethy, Shie Mannor

NeurIPS 2011 From Bandits to Experts: On the Value of Side-Observations Shie Mannor, Ohad Shamir

ICML 2011 Learning from Multiple Outlooks Maayan Harel, Shie Mannor

ICML 2011 Mean-Variance Optimization in Markov Decision Processes Shie Mannor, John N. Tsitsiklis

IJCAI 2011 Probabilistic Goal Markov Decision Processes Huan Xu, Shie Mannor

COLT 2011 Robust Approachability and Regret Minimization in Games with Partial Monitoring Shie Mannor, Vianney Perchet, Gilles Stoltz

JMLR 2011 The Sample Complexity of Dictionary Learning Daniel Vainsencher, Shie Mannor, Alfred M. Bruckstein

COLT 2011 The Sample Complexity of Dictionary Learning Daniel Vainsencher, Shie Mannor, Alfred M. Bruckstein

ICML 2011 Unimodal Bandits Jia Yuan Yu, Shie Mannor

AAAI 2010 Activity and Gait Recognition with Time-Delay Embeddings Jordan Frank, Shie Mannor, Doina Precup

ECML-PKDD 2010 Adaptive Bases for Reinforcement Learning Dotan Di Castro, Shie Mannor

NeurIPS 2010 Distributionally Robust Markov Decision Processes Huan Xu, Shie Mannor

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

NeurIPS 2010 Online Classification with Specificity Constraints Andrey Bernstein, Shie Mannor, Nahum Shimkin

COLT 2010 Principal Component Analysis with Contaminated Data: The High Dimensional Case Huan Xu, Constantine Caramanis, Shie Mannor

COLT 2010 Robustness and Generalization Huan Xu, Shie Mannor

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

JMLR 2009 Online Learning with Sample Path Constraints Shie Mannor, John N. Tsitsiklis, Jia Yuan Yu

ICML 2009 Piecewise-Stationary Bandit Problems with Side Observations Jia Yuan Yu, Shie Mannor

JMLR 2009 Robustness and Regularization of Support Vector Machines Huan Xu, Constantine Caramanis, Shie Mannor

COLT 2008 Learning in the Limit with Adversarial Disturbances Constantine Caramanis, Shie Mannor

AAAI 2008 Online Learning with Expert Advice and Finite-Horizon Constraints Branislav Kveton, Jia Yuan Yu, Georgios Theocharous, Shie Mannor

NeurIPS 2008 Regularized Policy Iteration Amir M. Farahmand, Mohammad Ghavamzadeh, Shie Mannor, Csaba Szepesvári

ICML 2008 Reinforcement Learning in the Presence of Rare Events Jordan Frank, Shie Mannor, Doina Precup

NeurIPS 2008 Robust Regression and Lasso Huan Xu, Constantine Caramanis, Shie Mannor

AAAI 2007 Adaptive Timeout Policies for Fast Fine-Grained Power Management Branislav Kveton, Prashant Gandhi, Georgios Theocharous, Shie Mannor, Barbara Rosario, Nilesh Shah

MLJ 2007 Online Calibrated Forecasts: Memory Efficiency Versus Universality for Learning in Games Shie Mannor, Jeff S. Shamma, Gürdal Arslan

ICML 2007 Percentile Optimization in Uncertain Markov Decision Processes with Application to Efficient Exploration Erick Delage, Shie Mannor

COLT 2007 Strategies for Prediction Under Imperfect Monitoring Gábor Lugosi, Shie Mannor, Gilles Stoltz

AAAI 2007 User Model and Utility Based Power Management Chih-Han Yu, Shie Mannor, Georgios Theocharous, Avi Pfeffer

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

ICML 2006 Automatic Basis Function Construction for Approximate Dynamic Programming and Reinforcement Learning Philipp W. Keller, Shie Mannor, Doina Precup

COLT 2006 Online Learning with Constraints Shie Mannor, John N. Tsitsiklis

COLT 2006 Online Learning with Variable Stage Duration Shie Mannor, Nahum Shimkin

NeurIPS 2006 The Robustness-Performance Tradeoff in Markov Decision Processes Huan Xu, Shie Mannor

ICML 2005 Reinforcement Learning with Gaussian Processes Yaakov Engel, Shie Mannor, Ron Meir

ICML 2005 The Cross Entropy Method for Classification Shie Mannor, Dori Peleg, Reuven Y. Rubinstein

JMLR 2004 A Geometric Approach to Multi-Criterion Reinforcement Learning Shie Mannor, Nahum Shimkin

COLT 2004 An Inequality for Nearly Log-Concave Distributions with Applications to Learning Constantine Caramanis, Shie Mannor

ICML 2004 Bias and Variance in Value Function Estimation Shie Mannor, Duncan Simester, Peng Sun, John N. Tsitsiklis

ICML 2004 Dynamic Abstraction in Reinforcement Learning via Clustering Shie Mannor, Ishai Menache, Amit Hoze, Uri Klein

COLT 2004 Reinforcement Learning for Average Reward Zero-Sum Games Shie Mannor

JMLR 2004 The Sample Complexity of Exploration in the Multi-Armed Bandit Problem (Special Topic on Learning Theory) Shie Mannor, John N. Tsitsiklis

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

ICML 2003 Bayes Meets Bellman: The Gaussian Process Approach to Temporal Difference Learning Yaakov Engel, Shie Mannor, Ron Meir

JMLR 2003 Greedy Algorithms for Classification -- Consistency, Convergence Rates, and Adaptivity Shie Mannor, Ron Meir, Tong Zhang

COLT 2003 Lower Bounds on the Sample Complexity of Exploration in the Multi-Armed Bandit Problem Shie Mannor, John N. Tsitsiklis

COLT 2003 On-Line Learning with Imperfect Monitoring Shie Mannor, Nahum Shimkin

ICML 2003 The Cross Entropy Method for Fast Policy Search Shie Mannor, Reuven Y. Rubinstein, Yohai Gat

MLJ 2002 On the Existence of Linear Weak Learners and Applications to Boosting Shie Mannor, Ron Meir

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

ECML-PKDD 2002 Q-Cut - Dynamic Discovery of Sub-Goals in Reinforcement Learning Ishai Menache, Shie Mannor, Nahum Shimkin

ECML-PKDD 2002 Sparse Online Greedy Support Vector Regression Yaakov Engel, Shie Mannor, Ron Meir

COLT 2002 The Consistency of Greedy Algorithms for Classification Shie Mannor, Ron Meir, Tong Zhang

COLT 2001 Adaptive Strategies and Regret Minimization in Arbitrarily Varying Markov Environments Shie Mannor, Nahum Shimkin

COLT 2001 Geometric Bounds for Generalization in Boosting Shie Mannor, Ron Meir

ICML 2001 Learning Embedded Maps of Markov Processes Yaakov Engel, Shie Mannor

NeurIPS 2001 The Steering Approach for Multi-Criteria Reinforcement Learning Shie Mannor, Nahum Shimkin

NeurIPS 2000 Weak Learners and Improved Rates of Convergence in Boosting Shie Mannor, Ron Meir