Petrik, Marek

53 publications

ICML 2025 Provable Policy Gradient for Robust Average-Reward MDPs Beyond Rectangularity Qiuhao Wang, Yuqi Zha, Chin Pang Ho, Marek Petrik

AISTATS 2025 Q-Learning for Quantile MDPs: A Decomposition, Performance, and Convergence Analysis Jia Lin Hau, Erick Delage, Esther Derman, Mohammad Ghavamzadeh, Marek Petrik

AAAI 2025 Risk-Averse Total-Reward MDPs with ERM and EVaR Xihong Su, Marek Petrik, Julien Grand-Clément

NeurIPS 2025 Risk-Averse Total-Reward Reinforcement Learning Xihong Su, Jia Lin Hau, Gersi Doko, Kishan Panaganti, Marek Petrik

ICML 2024 Bayesian Regret Minimization in Offline Bandits Marek Petrik, Guy Tennenholtz, Mohammad Ghavamzadeh

ICMLW 2024 Optimality of Stationary Policies in Risk-Averse Total-Reward MDPs with EVaR Xihong Su, Marek Petrik, Julien Grand-Clément

AISTATS 2023 Entropic Risk Optimization in Discounted MDPs Jia Lin Hau, Marek Petrik, Mohammad Ghavamzadeh

NeurIPSW 2023 Non-Adaptive Online Finetuning for Offline Reinforcement Learning Audrey Huang, Mohammad Ghavamzadeh, Nan Jiang, Marek Petrik

NeurIPS 2023 On Dynamic Programming Decompositions of Static Risk Measures in Markov Decision Processes Jia Lin Hau, Erick Delage, Mohammad Ghavamzadeh, Marek Petrik

NeurIPS 2023 Percentile Criterion Optimization in Offline Reinforcement Learning Cyrus Cousins, Elita Lobo, Marek Petrik, Yair Zick

ICML 2023 Policy Gradient in Robust MDPs with Global Convergence Guarantee Qiuhao Wang, Chin Pang Ho, Marek Petrik

NeurIPS 2023 Reducing Blackwell and Average Optimality to Discounted MDPs via the Blackwell Discount Factor Julien Grand-Clément, Marek Petrik

UAI 2023 Solving Multi-Model MDPs by Coordinate Ascent and Dynamic Programming Xihong Su, Marek Petrik

ICLRW 2022 Data Poisoning Attacks on Off-Policy Policy Evaluation Algorithms Elita Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin, Himabindu Lakkaraju

UAI 2022 Data Poisoning Attacks on Off-Policy Policy Evaluation Methods Elita Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin, Himabindu Lakkaraju

NeurIPS 2022 Robust $\phi$-Divergence MDPs Chin Pang Ho, Marek Petrik, Wolfram Wiesemann

AISTATS 2021 Optimizing Percentile Criterion Using Robust MDPs Bahram Behzadian, Reazul Hasan Russel, Marek Petrik, Chin Pang Ho

NeurIPS 2021 Fast Algorithms for $L_\infty$-Constrained S-Rectangular Robust MDPs Bahram Behzadian, Marek Petrik, Chin Pang Ho

JMLR 2021 Partial Policy Iteration for L1-Robust Markov Decision Processes Chin Pang Ho, Marek Petrik, Wolfram Wiesemann

ICML 2021 Policy Gradient Bayesian Robust Optimization for Imitation Learning Zaynah Javed, Daniel S Brown, Satvik Sharma, Jerry Zhu, Ashwin Balakrishna, Marek Petrik, Anca Dragan, Ken Goldberg

NeurIPS 2020 Bayesian Robust Optimization for Imitation Learning Daniel Brown, Scott Niekum, Marek Petrik

AAAI 2020 Beliefs We Can Believe in: Replacing Assumptions with Data in Real-Time Search Maximilian Fickert, Tianyi Gu, Leonhard Staut, Wheeler Ruml, Jörg Hoffmann, Marek Petrik

NeurIPS 2019 Beyond Confidence Regions: Tight Bayesian Ambiguity Sets for Robust MDPs Marek Petrik, Reazul Hasan Russel

AAAI 2019 Real-Time Planning as Decision-Making Under Uncertainty Andrew Mitchell, Wheeler Ruml, Fabian Spaniol, Jörg Hoffmann, Marek Petrik

ICML 2018 Fast Bellman Updates for Robust MDPs Chin Pang Ho, Marek Petrik, Wolfram Wiesemann

NeurIPS 2018 Policy-Conditioned Uncertainty Sets for Robust Markov Decision Processes Andrea Tirinzoni, Marek Petrik, Xiangli Chen, Brian Ziebart

JAIR 2018 Proximal Gradient Temporal Difference Learning: Stable Reinforcement Learning with Polynomial Sample Complexity Bo Liu, Ian Gemp, Mohammad Ghavamzadeh, Ji Liu, Sridhar Mahadevan, Marek Petrik

UAI 2017 A Practical Method for Solving Contextual Bandit Problems Using Decision Trees Adam N. Elmachtoub, Ryan McNellis, Sechan Oh, Marek Petrik

AAAI 2017 Robust Partially-Compressed Least-Squares Stephen Becker, Ban Kawas, Marek Petrik

UAI 2017 Value Directed Exploration in Multi-Armed Bandits with Structured Priors Bence Cserna, Marek Petrik, Reazul Hasan Russel, Wheeler Ruml

UAI 2016 Interpretable Policies for Dynamic Product Recommendations Marek Petrik, Ronny Luss

IJCAI 2016 Proximal Gradient Temporal Difference Learning Algorithms Bo Liu, Ji Liu, Mohammad Ghavamzadeh, Sridhar Mahadevan, Marek Petrik

NeurIPS 2016 Safe Policy Improvement by Minimizing Robust Baseline Regret Mohammad Ghavamzadeh, Marek Petrik, Yinlam Chow

UAI 2015 Finite-Sample Analysis of Proximal Gradient TD Algorithms Bo Liu, Ji Liu, Mohammad Ghavamzadeh, Sridhar Mahadevan, Marek Petrik

UAI 2015 Optimal Threshold Control for Energy Arbitrage with Degradable Battery Storage Marek Petrik, Xiaojian Wu

JMLR 2014 Efficient and Accurate Methods for Updating Generalized Linear Models with Multiple Feature Additions Amit Dhurandhar, Marek Petrik

NeurIPS 2014 RAAM: The Benefits of Robustness in Approximating Aggregated MDPs in Reinforcement Learning Marek Petrik, Dharmashankar Subramanian

UAI 2013 Solution Methods for Constrained Markov Decision Process with Continuous Probability Modulation Marek Petrik, Dharmashankar Subramanian, Janusz Marecki

UAI 2012 An Approximate Solution Method for Large Risk-Averse Markov Decision Processes Marek Petrik, Dharmashankar Subramanian

ICML 2012 Approximate Dynamic Programming by Minimizing Distributionally Robust Bounds Marek Petrik

AAAI 2011 Linear Dynamic Programs for Resource Management Marek Petrik, Shlomo Zilberstein

JMLR 2011 Robust Approximate Bilinear Programming for Value Function Approximation Marek Petrik, Shlomo Zilberstein

ICML 2010 Feature Selection Using Regularization in Approximate Linear Programs for Markov Decision Processes Marek Petrik, Gavin Taylor, Ronald Parr, Shlomo Zilberstein

JAIR 2009 A Bilinear Programming Approach for Multiagent Planning Marek Petrik, Shlomo Zilberstein

ICML 2009 Constraint Relaxation in Approximate Linear Programs Marek Petrik, Shlomo Zilberstein

ECML-PKDD 2009 Hybrid Least-Squares Algorithms for Approximate Policy Evaluation Jeffrey Johns, Marek Petrik, Sridhar Mahadevan

MLJ 2009 Hybrid Least-Squares Algorithms for Approximate Policy Evaluation Jeffrey Johns, Marek Petrik, Sridhar Mahadevan

NeurIPS 2009 Robust Value Function Approximation Using Bilinear Programming Marek Petrik, Shlomo Zilberstein

NeurIPS 2008 Biasing Approximate Dynamic Programming with a Lower Discount Factor Marek Petrik, Bruno Scherrer

AAAI 2008 Interaction Structure and Dimensionality Reduction in Decentralized MDPs Martin Allen, Marek Petrik, Shlomo Zilberstein

IJCAI 2007 An Analysis of Laplacian Methods for Value Function Approximation in MDPs Marek Petrik

AAAI 2007 Anytime Coordination Using Separable Bilinear Programs Marek Petrik, Shlomo Zilberstein

IJCAI 2007 Average-Reward Decentralized Markov Decision Processes Marek Petrik, Shlomo Zilberstein