Mohammad Ghavamzadeh

233 papers A* 61A 18B 3C 3Misc 2Journal 119Unranked 25

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	$$\texttt{C2-DPO}$$: Constrained Controlled Direct Preference Optimization. Trans. Mach. Learn. Res. Kavosh Asadi, Xingzi Xu, Julien Han, Ege Beyazit, Idan Pipano, Dominique Perrault-Joncas, Shoham Sabach, Mohammad Ghavamzadeh, Karim Bouyarmane
2026	J	`jnl`	Beyond Binary Preferences: A Principled Framework for Reward Modeling with Ordinal Feedback. CoRR Amirhossein Afsharrad, Ruida Zhou, Luca Viano, Sanjay Lall, Mohammad Ghavamzadeh
2026	J	`jnl`	DISPO: Enhancing Training Efficiency and Stability in Reinforcement Learning for Large Language Model Mathematical Reasoning. CoRR Batuhan K. Karaman, Aditya Rawal, Suhaila Shakiah, Mohammad Ghavamzadeh, Mingyi Hong, Arijit Biswas, Ruida Zhou
2026	J	`jnl`	Direct Preference Optimization with Rating Information: Practical Algorithms and Provable Gains. CoRR Luca Viano, Ruida Zhou, Yifan Sun, Mahdi Namazifar, Volkan Cevher, Shoham Sabach, Mohammad Ghavamzadeh
2026	J	`jnl`	Displacement-Resistant Extensions of DPO with Nonconvex CoRR Idan Pipano, Shoham Sabach, Kavosh Asadi, Mohammad Ghavamzadeh
2026	A*	`conf`	Preference Optimization via Contrastive Divergence: Your Policy Is Secretly an NLL Estimator. AAAI Zhuotong Chen, Fang Liu, Xuan Zhu, Haozhu Wang, Jiayu Li, Yanjun Qi, Mohammad Ghavamzadeh
2025	—	`conf`	Bridging Distributionally Robust Learning and Offline RL: An Approach to Mitigate Distribution Shift and Partial Data Coverage. L4DC Kishan Panaganti, Zaiyan Xu, Dileep Kalathil, Mohammad Ghavamzadeh
2025	J	`jnl`	C-3DPO: Constrained Controlled Classification for Direct Preference Optimization. CoRR Kavosh Asadi, Julien Han, Xingzi Xu, Dominique Perrault-Joncas, Shoham Sabach, Karim Bouyarmane, Mohammad Ghavamzadeh
2025	A*	`conf`	Conservative Contextual Bandits: Beyond Linear Representations. ICLR Rohan Deb, Mohammad Ghavamzadeh, Arindam Banerjee
2025	J	`jnl`	Contextual Bandits with Stage-wise Constraints. J. Mach. Learn. Res. Aldo Pacchiano, Mohammad Ghavamzadeh, Peter L. Bartlett
2025	J	`jnl`	Diffusion Blend: Inference-Time Multi-Preference Alignment for Diffusion Models. CoRR Min Cheng, Fatemeh Doudi, Dileep Kalathil, Mohammad Ghavamzadeh, Panganamala R. Kumar
2025	J	`jnl`	Directional-Clamp PPO. CoRR Gilad Karpel, Ruida Zhou, Shoham Sabach, Mohammad Ghavamzadeh
2025	J	`jnl`	Does Thinking More always Help? Understanding Test-Time Scaling in Reasoning Models. CoRR Soumya Suvra Ghosal, Souradip Chakraborty, Avinash Reddy, Yifu Lu, Mengdi Wang, Dinesh Manocha, Furong Huang, Mohammad Ghavamzadeh, Amrit Singh Bedi
2025	J	`jnl`	Ordering-based Conditions for Global Convergence of Policy Gradient Methods. CoRR Jincheng Mei, Bo Dai, Alekh Agarwal, Mohammad Ghavamzadeh, Csaba Szepesvári, Dale Schuurmans
2025	J	`jnl`	Preference Optimization via Contrastive Divergence: Your Reward Model is Secretly an NLL Estimator. CoRR Zhuotong Chen, Fang Liu, Xuan Zhu, Yanjun Qi, Mohammad Ghavamzadeh
2025	A	`conf`	Q-learning for Quantile MDPs: A Decomposition, Performance, and Convergence Analysis. AISTATS Jia Lin Hau, Erick Delage, Esther Derman, Mohammad Ghavamzadeh, Marek Petrik
2025	J	`jnl`	Synthetic Dialogue Generation for Interactive Conversational Elicitation & Recommendation (ICER). CoRR Moonkyung Ryu, Chih-Wei Hsu, Yinlam Chow, Mohammad Ghavamzadeh, Craig Boutilier
2024	A*	`conf`	Bayesian Regret Minimization in Offline Bandits. ICML Marek Petrik, Guy Tennenholtz, Mohammad Ghavamzadeh
2024	A*	`conf`	Confidence-aware Reward Optimization for Fine-tuning Text-to-Image Models. ICLR Kyuyoung Kim, Jongheon Jeong, Minyong An, Mohammad Ghavamzadeh, Krishnamurthy Dj Dvijotham, Jinwoo Shin, Kimin Lee
2024	J	`jnl`	Confidence-aware Reward Optimization for Fine-tuning Text-to-Image Models. CoRR Kyuyoung Kim, Jongheon Jeong, Minyong An, Mohammad Ghavamzadeh, Krishnamurthy Dvijotham, Jinwoo Shin, Kimin Lee
2024	J	`jnl`	Conservative Contextual Bandits: Beyond Linear Representations. CoRR Rohan Deb, Mohammad Ghavamzadeh, Arindam Banerjee
2024	J	`jnl`	Contextual Bandits with Stage-wise Constraints. CoRR Aldo Pacchiano, Mohammad Ghavamzadeh, Peter L. Bartlett
2024	J	`jnl`	Discovering Personalized Semantics for Soft Attributes in Recommender Systems Using Concept Activation Vectors. Trans. Recomm. Syst. Christina Göpfert, Alex Haig, Chih-Wei Hsu, Yinlam Chow, Ivan Vendrov, Tyler Lu, Deepak Ramachandran, Hubert Pham, Mohammad Ghavamzadeh, Craig Boutilier
2024	A*	`conf`	Maximum Entropy Model Correction in Reinforcement Learning. ICLR Amin Rakhsha, Mete Kemertas, Mohammad Ghavamzadeh, Amir-massoud Farahmand
2024	J	`jnl`	Non-adaptive Online Finetuning for Offline Reinforcement Learning. RLJ Audrey Huang, Mohammad Ghavamzadeh, Nan Jiang, Marek Petrik
2024	J	`jnl`	Non-stationary Bandits and Meta-Learning with a Small Set of Optimal Arms. RLJ Mohammad Javad Azizi, Thang Duong, Yasin Abbasi-Yadkori, András György, Claire Vernade, Mohammad Ghavamzadeh
2024	J	`jnl`	Q-learning for Quantile MDPs: A Decomposition, Performance, and Convergence Analysis. CoRR Jia Lin Hau, Erick Delage, Esther Derman, Mohammad Ghavamzadeh, Marek Petrik
2023	J	`jnl`	A Convex Relaxation Approach to Bayesian Regret Minimization in Offline Bandits. CoRR Mohammad Ghavamzadeh, Marek Petrik, Guy Tennenholtz
2023	A*	`conf`	A Mixture-of-Expert Approach to RL-based Dialogue Management. ICLR Yinlam Chow, Aza Tulepbergenov, Ofir Nachum, Dhawal Gupta, Moonkyung Ryu, Mohammad Ghavamzadeh, Craig Boutilier
2023	J	`jnl`	A Review of Deep Learning for Video Captioning. CoRR Moloud Abdar, Meenakshi Kollati, Swaraja Kuraparthi, Farhad Pourpanah, Daniel McDuff, Mohammad Ghavamzadeh, Shuicheng Yan, Abduallah Mohamed, Abbas Khosravi, Erik Cambria, Fatih Porikli
2023	J	`jnl`	Aligning Text-to-Image Models using Human Feedback. CoRR Kimin Lee, Hao Liu, Moonkyung Ryu, Olivia Watkins, Yuqing Du, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Shixiang Shane Gu
2023	J	`jnl`	Bridging Distributionally Robust Learning and Offline RL: An Approach to Mitigate Distribution Shift and Partial Data Coverage. CoRR Kishan Panaganti, Zaiyan Xu, Dileep M. Kalathil, Mohammad Ghavamzadeh
2023	J	`jnl`	DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models. CoRR Ying Fan, Olivia Watkins, Yuqing Du, Hao Liu, Moonkyung Ryu, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Kangwook Lee, Kimin Lee
2023	—	`conf`	Distributionally Robust Behavioral Cloning for Robust Imitation Learning. CDC Kishan Panaganti, Zaiyan Xu, Dileep Kalathil, Mohammad Ghavamzadeh
2023	A	`conf`	Entropic Risk Optimization in Discounted MDPs. AISTATS Jia Lin Hau, Marek Petrik, Mohammad Ghavamzadeh
2023	J	`jnl`	Factual and Personalized Recommendations using Language Models and Reinforcement Learning. CoRR Jihwan Jeong, Yinlam Chow, Guy Tennenholtz, Chih-Wei Hsu, Azamat Tulepbergenov, Mohammad Ghavamzadeh, Craig Boutilier
2023	J	`jnl`	Maximum Entropy Model Correction in Reinforcement Learning. CoRR Amin Rakhsha, Mete Kemertas, Mohammad Ghavamzadeh, Amir-massoud Farahmand
2023	A*	`conf`	Meta-Learning for Simple Regret Minimization. AAAI Mohammad Javad Azizi, Branislav Kveton, Mohammad Ghavamzadeh, Sumeet Katariya
2023	A*	`conf`	Multi-Task Off-Policy Learning from Bandit Feedback. ICML Joey Hong, Branislav Kveton, Manzil Zaheer, Sumeet Katariya, Mohammad Ghavamzadeh
2023	A	`conf`	Multiple-policy High-confidence Policy Evaluation. AISTATS Christoph Dann, Mohammad Ghavamzadeh, Teodor V. Marinov
2023	A*	`conf`	Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management. NeurIPS Dhawal Gupta, Yinlam Chow, Azamat Tulepbergenov, Mohammad Ghavamzadeh, Craig Boutilier
2023	J	`jnl`	Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management. CoRR Dhawal Gupta, Yinlam Chow, Mohammad Ghavamzadeh, Craig Boutilier
2023	J	`jnl`	On Dynamic Program Decompositions of Static Risk Measures. CoRR Jia Lin Hau, Erick Delage, Mohammad Ghavamzadeh, Marek Petrik
2023	A*	`conf`	On Dynamic Programming Decompositions of Static Risk Measures in Markov Decision Processes. NeurIPS Jia Lin Hau, Erick Delage, Mohammad Ghavamzadeh, Marek Petrik
2023	A*	`conf`	Ordering-based Conditions for Global Convergence of Policy Gradient Methods. NeurIPS Jincheng Mei, Bo Dai, Alekh Agarwal, Mohammad Ghavamzadeh, Csaba Szepesvári, Dale Schuurmans
2023	J	`jnl`	Preference Elicitation with Soft Attributes in Interactive Recommendation. CoRR Erdem Biyik, Fan Yao, Yinlam Chow, Alex Haig, Chih-Wei Hsu, Mohammad Ghavamzadeh, Craig Boutilier
2023	J	`jnl`	Private and Communication-Efficient Algorithms for Entropy Estimation. CoRR Gecia Bravo Hermsdorff, Róbert Busa-Fekete, Mohammad Ghavamzadeh, Andres Muñoz Medina, Umar Syed
2023	A*	`conf`	Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models. NeurIPS Ying Fan, Olivia Watkins, Yuqing Du, Hao Liu, Moonkyung Ryu, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Kangwook Lee, Kimin Lee
2022	J	`jnl`	A Mixture-of-Expert Approach to RL-based Dialogue Management. CoRR Yinlam Chow, Aza Tulepbergenov, Ofir Nachum, Moonkyung Ryu, Mohammad Ghavamzadeh, Craig Boutilier
2022	C	`conf`	Collaborative Multi-agent Stochastic Linear Bandits. ACC Ahmadreza Moradipari, Mohammad Ghavamzadeh, Mahnoosh Alizadeh
2022	J	`jnl`	Collaborative Multi-agent Stochastic Linear Bandits. CoRR Ahmadreza Moradipari, Mohammad Ghavamzadeh, Mahnoosh Alizadeh
2022	A*	`conf`	Deep Hierarchy in Bandits. ICML Joey Hong, Branislav Kveton, Sumeet Katariya, Manzil Zaheer, Mohammad Ghavamzadeh
2022	J	`jnl`	Deep Hierarchy in Bandits. CoRR Joey Hong, Branislav Kveton, Sumeet Katariya, Manzil Zaheer, Mohammad Ghavamzadeh
2022	A*	`conf`	Efficient Risk-Averse Reinforcement Learning. NeurIPS Ido Greenberg, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor
2022	J	`jnl`	Efficient Risk-Averse Reinforcement Learning. CoRR Ido Greenberg, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor
2022	A*	`conf`	Feature and Parameter Selection in Stochastic Linear Bandits. ICML Ahmadreza Moradipari, Berkay Turan, Yasin Abbasi-Yadkori, Mahnoosh Alizadeh, Mohammad Ghavamzadeh
2022	A*	`conf`	Fixed-Budget Best-Arm Identification in Structured Bandits. IJCAI Mohammad Javad Azizi, Branislav Kveton, Mohammad Ghavamzadeh
2022	A	`conf`	Hierarchical Bayesian Bandits. AISTATS Joey Hong, Branislav Kveton, Manzil Zaheer, Mohammad Ghavamzadeh
2022	J	`jnl`	Meta-Learning for Simple Regret Minimization. CoRR Mohammad Javad Azizi, Branislav Kveton, Mohammad Ghavamzadeh, Sumeet Katariya
2022	A*	`conf`	Mirror Descent Policy Optimization. ICLR Manan Tomar, Lior Shani, Yonathan Efroni, Mohammad Ghavamzadeh
2022	B	`conf`	Multi-Environment Meta-Learning in Stochastic Linear Bandits. ISIT Ahmadreza Moradipari, Mohammad Ghavamzadeh, Taha Rajabzadeh, Christos Thrampoulidis, Mahnoosh Alizadeh
2022	J	`jnl`	Multi-Environment Meta-Learning in Stochastic Linear Bandits. CoRR Ahmadreza Moradipari, Mohammad Ghavamzadeh, Taha Rajabzadeh, Christos Thrampoulidis, Mahnoosh Alizadeh
2022	J	`jnl`	Multi-Task Off-Policy Learning from Bandit Feedback. CoRR Joey Hong, Branislav Kveton, Sumeet Katariya, Manzil Zaheer, Mohammad Ghavamzadeh
2022	J	`jnl`	Non-stationary Bandits and Meta-Learning with a Small Set of Optimal Arms. CoRR Mohammad Javad Azizi, Thang Duong, Yasin Abbasi-Yadkori, András György, Claire Vernade, Mohammad Ghavamzadeh
2022	A*	`conf`	Operator Splitting Value Iteration. NeurIPS Amin Rakhsha, Andrew Wang, Mohammad Ghavamzadeh, Amir-massoud Farahmand
2022	J	`jnl`	Operator Splitting Value Iteration. CoRR Amin Rakhsha, Andrew Wang, Mohammad Ghavamzadeh, Amir-massoud Farahmand
2022	A*	`conf`	Private and Communication-Efficient Algorithms for Entropy Estimation. NeurIPS Gecia Bravo Hermsdorff, Róbert Busa-Fekete, Mohammad Ghavamzadeh, Andrés Muñoz Medina, Umar Syed
2022	J	`jnl`	RASR: Risk-Averse Soft-Robust MDPs with EVaR and Entropic Risk. CoRR Jia Lin Hau, Marek Petrik, Mohammad Ghavamzadeh, Reazul Hasan Russel
2022	J	`jnl`	Reinforcement Learning of Multi-Domain Dialog Policies Via Action Embeddings. CoRR Jorge A. Mendez, Alborz Geramifard, Mohammad Ghavamzadeh, Bing Liu
2022	A*	`conf`	Robust Reinforcement Learning using Offline Data. NeurIPS Kishan Panaganti, Zaiyan Xu, Dileep Kalathil, Mohammad Ghavamzadeh
2022	J	`jnl`	Robust Reinforcement Learning using Offline Data. CoRR Kishan Panaganti, Zaiyan Xu, Dileep M. Kalathil, Mohammad Ghavamzadeh
2022	A	`conf`	Thompson Sampling with a Mixture Prior. AISTATS Joey Hong, Branislav Kveton, Manzil Zaheer, Mohammad Ghavamzadeh, Craig Boutilier
2021	J	`jnl`	A review of uncertainty quantification in deep learning: Techniques, applications and challenges. Inf. Fusion Moloud Abdar, Farhad Pourpanah, Sadiq Hussain, Dana Rezazadegan, Li Liu, Mohammad Ghavamzadeh, Paul W. Fieguth, Xiaochun Cao, Abbas Khosravi, U. Rajendra Acharya, Vladimir Makarenkov, Saeid Nahavandi
2021	J	`jnl`	Active Learning for Classification With Abstention. IEEE J. Sel. Areas Inf. Theory Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi
2021	A*	`conf`	Adaptive Sampling for Minimax Fair Classification. NeurIPS Shubhanshu Shekhar, Greg Fields, Mohammad Ghavamzadeh, Tara Javidi
2021	J	`jnl`	Adaptive Sampling for Minimax Fair Classification. CoRR Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi
2021	A*	`conf`	Control-Aware Representations for Model-based Reinforcement Learning. ICLR Brandon Cui, Yinlam Chow, Mohammad Ghavamzadeh
2021	A*	`conf`	Deep Bayesian Quadrature Policy Optimization. AAAI Ravi Tej Akella, Kamyar Azizzadenesheli, Mohammad Ghavamzadeh, Animashree Anandkumar, Yisong Yue
2021	J	`jnl`	Fixed-Budget Best-Arm Identification in Contextual Bandits: A Static-Adaptive Algorithm. CoRR Mohammad Javad Azizi, Branislav Kveton, Mohammad Ghavamzadeh
2021	J	`jnl`	Hierarchical Bayesian Bandits. CoRR Joey Hong, Branislav Kveton, Manzil Zaheer, Mohammad Ghavamzadeh
2021	—	`conf`	Neural Lyapunov Redesign. L4DC Arash Mehrjou, Mohammad Ghavamzadeh, Bernhard Schölkopf
2021	A*	`conf`	PID Accelerated Value Iteration Algorithm. ICML Amir Massoud Farahmand, Mohammad Ghavamzadeh
2021	J	`jnl`	Parameter and Feature Selection in Stochastic Linear Bandits. CoRR Ahmadreza Moradipari, Yasin Abbasi-Yadkori, Mahnoosh Alizadeh, Mohammad Ghavamzadeh
2021	A	`conf`	Stochastic Bandits with Linear Constraints. AISTATS Aldo Pacchiano, Mohammad Ghavamzadeh, Peter L. Bartlett, Heinrich Jiang
2021	J	`jnl`	Thompson Sampling with a Mixture Prior. CoRR Joey Hong, Branislav Kveton, Manzil Zaheer, Mohammad Ghavamzadeh, Craig Boutilier
2021	A*	`conf`	Variational Model-based Policy Optimization. IJCAI Yinlam Chow, Brandon Cui, Moonkyung Ryu, Mohammad Ghavamzadeh
2020	J	`jnl`	A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges. CoRR Moloud Abdar, Farhad Pourpanah, Sadiq Hussain, Dana Rezazadegan, Li Liu, Mohammad Ghavamzadeh, Paul W. Fieguth, Xiaochun Cao, Abbas Khosravi, U. Rajendra Acharya, Vladimir Makarenkov, Saeid Nahavandi
2020	B	`conf`	Active Learning for Classification with Abstention. ISIT Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi
2020	A	`conf`	Active Model Estimation in Markov Decision Processes. UAI Jean Tarbouriech, Shubhanshu Shekhar, Matteo Pirotta, Mohammad Ghavamzadeh, Alessandro Lazaric
2020	J	`jnl`	Active Model Estimation in Markov Decision Processes. CoRR Jean Tarbouriech, Shubhanshu Shekhar, Matteo Pirotta, Mohammad Ghavamzadeh, Alessandro Lazaric
2020	A*	`conf`	Adaptive Sampling for Estimating Probability Distributions. ICML Shubhanshu Shekhar, Tara Javidi, Mohammad Ghavamzadeh
2020	J	`jnl`	Automatic Policy Synthesis to Improve the Safety of Nonlinear Dynamical Systems. CoRR Arash Mehrjou, Mohammad Ghavamzadeh, Bernhard Schölkopf
2020	A	`conf`	Conservative Exploration in Reinforcement Learning. AISTATS Evrard Garcelon, Mohammad Ghavamzadeh, Alessandro Lazaric, Matteo Pirotta
2020	J	`jnl`	Conservative Exploration in Reinforcement Learning. CoRR Evrard Garcelon, Mohammad Ghavamzadeh, Alessandro Lazaric, Matteo Pirotta
2020	J	`jnl`	Control-Aware Representations for Model-based Reinforcement Learning. CoRR Brandon Cui, Yinlam Chow, Mohammad Ghavamzadeh
2020	J	`jnl`	Deep Bayesian Quadrature Policy Optimization. CoRR Ravi Tej Akella, Kamyar Azizzadenesheli, Mohammad Ghavamzadeh, Anima Anandkumar, Yisong Yue
2020	J	`jnl`	Finite-Sample Analysis of GTD Algorithms. CoRR Bo Liu, Ji Liu, Mohammad Ghavamzadeh, Sridhar Mahadevan, Marek Petrik
2020	A*	`conf`	Improved Algorithms for Conservative Exploration in Bandits. AAAI Evrard Garcelon, Mohammad Ghavamzadeh, Alessandro Lazaric, Matteo Pirotta
2020	J	`jnl`	Improved Algorithms for Conservative Exploration in Bandits. CoRR Evrard Garcelon, Mohammad Ghavamzadeh, Alessandro Lazaric, Matteo Pirotta
2020	J	`jnl`	Mirror Descent Policy Optimization. CoRR Manan Tomar, Lior Shani, Yonathan Efroni, Mohammad Ghavamzadeh
2020	A*	`conf`	Multi-step Greedy Reinforcement Learning Algorithms. ICML Manan Tomar, Yonathan Efroni, Mohammad Ghavamzadeh
2020	J	`jnl`	Non-Stationary Latent Bandits. CoRR Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed, Mohammad Ghavamzadeh, Craig Boutilier
2020	A*	`conf`	Online Planning with Lookahead Policies. NeurIPS Yonathan Efroni, Mohammad Ghavamzadeh, Shie Mannor
2020	J	`jnl`	Policy-Aware Model Learning for Policy Gradient Methods. CoRR Romina Abachi, Mohammad Ghavamzadeh, Amir-massoud Farahmand
2020	A*	`conf`	Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control. ICLR Nir Levine, Yinlam Chow, Rui Shu, Ang Li, Mohammad Ghavamzadeh, Hung Bui
2020	A*	`conf`	Predictive Coding for Locally-Linear Control. ICML Rui Shu, Tung Nguyen, Yinlam Chow, Tuan Pham, Khoat Than, Mohammad Ghavamzadeh, Stefano Ermon, Hung H. Bui
2020	J	`jnl`	Predictive Coding for Locally-Linear Control. CoRR Rui Shu, Tung Nguyen, Yinlam Chow, Tuan Pham, Khoat Than, Mohammad Ghavamzadeh, Stefano Ermon, Hung H. Bui
2020	J	`jnl`	Proximal Gradient Temporal Difference Learning: Stable Reinforcement Learning with Polynomial Sample Complexity. CoRR Bo Liu, Ian Gemp, Mohammad Ghavamzadeh, Ji Liu, Sridhar Mahadevan, Marek Petrik
2020	A	`conf`	Randomized Exploration in Generalized Linear Bandits. AISTATS Branislav Kveton, Manzil Zaheer, Csaba Szepesvári, Lihong Li, Mohammad Ghavamzadeh, Craig Boutilier
2020	Misc	`conf`	Safe Policy Learning for Continuous Control. CoRL Yinlam Chow, Ofir Nachum, Aleksandra Faust, Edgar A. Duéñez-Guzmán, Mohammad Ghavamzadeh
2020	J	`jnl`	Soft-Robust Algorithms for Handling Model Misspecification. CoRR Elita A. Lobo, Mohammad Ghavamzadeh, Marek Petrik
2020	J	`jnl`	Stochastic Bandits with Linear Constraints. CoRR Aldo Pacchiano, Mohammad Ghavamzadeh, Peter L. Bartlett, Heinrich Jiang
2020	J	`jnl`	Variance-Reduced Off-Policy Memory-Efficient Policy Search. CoRR Daoming Lyu, Qi Qi, Mohammad Ghavamzadeh, Hengshuai Yao, Tianbao Yang, Bo Liu
2020	J	`jnl`	Variational Model-based Policy Optimization. CoRR Yinlam Chow, Brandon Cui, Moonkyung Ryu, Mohammad Ghavamzadeh
2019	J	`jnl`	Active Learning for Binary Classification with Abstention. CoRR Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi
2019	J	`jnl`	Adaptive Sampling for Estimating Multiple Probability Distributions. CoRR Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi
2019	J	`jnl`	Benchmarking Batch Deep Reinforcement Learning Algorithms. CoRR Scott Fujimoto, Edoardo Conti, Mohammad Ghavamzadeh, Joelle Pineau
2019	J	`jnl`	Binary Classification with Bounded Abstention Rate. CoRR Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi
2019	A*	`conf`	Garbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits. ICML Branislav Kveton, Csaba Szepesvári, Sharan Vaswani, Zheng Wen, Tor Lattimore, Mohammad Ghavamzadeh
2019	J	`jnl`	Lyapunov-based Safe Policy Optimization for Continuous Control. CoRR Yinlam Chow, Ofir Nachum, Aleksandra Faust, Mohammad Ghavamzadeh, Edgar A. Duéñez-Guzmán
2019	J	`jnl`	Multi-Step Greedy and Approximate Real Time Dynamic Programming. CoRR Yonathan Efroni, Mohammad Ghavamzadeh, Shie Mannor
2019	J	`jnl`	Multi-step Greedy Policies in Model-Free Deep Reinforcement Learning. CoRR Manan Tomar, Yonathan Efroni, Mohammad Ghavamzadeh
2019	A	`conf`	Optimizing over a Restricted Policy Class in MDPs. AISTATS Ershad Banijamali, Yasin Abbasi-Yadkori, Mohammad Ghavamzadeh, Nikos Vlassis
2019	A	`conf`	Perturbed-History Exploration in Stochastic Linear Bandits. UAI Branislav Kveton, Csaba Szepesvári, Mohammad Ghavamzadeh, Craig Boutilier
2019	J	`jnl`	Perturbed-History Exploration in Stochastic Linear Bandits. CoRR Branislav Kveton, Csaba Szepesvári, Mohammad Ghavamzadeh, Craig Boutilier
2019	A*	`conf`	Perturbed-History Exploration in Stochastic Multi-Armed Bandits. IJCAI Branislav Kveton, Csaba Szepesvári, Mohammad Ghavamzadeh, Craig Boutilier
2019	J	`jnl`	Perturbed-History Exploration in Stochastic Multi-Armed Bandits. CoRR Branislav Kveton, Csaba Szepesvári, Mohammad Ghavamzadeh, Craig Boutilier
2019	J	`jnl`	Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control. CoRR Nir Levine, Yinlam Chow, Rui Shu, Ang Li, Mohammad Ghavamzadeh, Hung Bui
2019	J	`jnl`	Randomized Exploration in Generalized Linear Bandits. CoRR Branislav Kveton, Manzil Zaheer, Csaba Szepesvári, Lihong Li, Mohammad Ghavamzadeh, Craig Boutilier
2019	A	`conf`	Risk-Sensitive Generative Adversarial Imitation Learning. AISTATS Jonathan Lacotte, Mohammad Ghavamzadeh, Yinlam Chow, Marco Pavone
2019	A*	`conf`	Tight Regret Bounds for Model-Based Reinforcement Learning with Greedy Policies. NeurIPS Yonathan Efroni, Nadav Merlis, Mohammad Ghavamzadeh, Shie Mannor
2019	J	`jnl`	Tight Regret Bounds for Model-Based Reinforcement Learning with Greedy Policies. CoRR Yonathan Efroni, Nadav Merlis, Mohammad Ghavamzadeh, Shie Mannor
2018	A*	`conf`	A Block Coordinate Ascent Algorithm for Mean-Variance Optimization. NeurIPS Tengyang Xie, Bo Liu, Yangyang Xu, Mohammad Ghavamzadeh, Yinlam Chow, Daoming Lyu, Daesub Yoon
2018	J	`jnl`	A Block Coordinate Ascent Algorithm for Mean-Variance Optimization. CoRR Bo Liu, Tengyang Xie, Yangyang Xu, Mohammad Ghavamzadeh, Yinlam Chow, Daoming Lyu, Daesub Yoon
2018	A*	`conf`	A Lyapunov-based Approach to Safe Reinforcement Learning. NeurIPS Yinlam Chow, Ofir Nachum, Edgar A. Duéñez-Guzmán, Mohammad Ghavamzadeh
2018	J	`jnl`	A Lyapunov-based Approach to Safe Reinforcement Learning. CoRR Yinlam Chow, Ofir Nachum, Edgar A. Duéñez-Guzmán, Mohammad Ghavamzadeh
2018	J	`jnl`	Garbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits. CoRR Branislav Kveton, Csaba Szepesvári, Zheng Wen, Mohammad Ghavamzadeh, Tor Lattimore
2018	A*	`conf`	More Robust Doubly Robust Off-policy Evaluation. ICML Mehrdad Farajtabar, Yinlam Chow, Mohammad Ghavamzadeh
2018	J	`jnl`	More Robust Doubly Robust Off-policy Evaluation. CoRR Mehrdad Farajtabar, Yinlam Chow, Mohammad Ghavamzadeh
2018	J	`jnl`	Optimizing over a Restricted Policy Class in Markov Decision Processes. CoRR Ershad Banijamali, Yasin Abbasi-Yadkori, Mohammad Ghavamzadeh, Nikos Vlassis
2018	Misc	`conf`	PAC Bandits with Risk Constraints. ISAIM Yahel David, Balázs Szörényi, Mohammad Ghavamzadeh, Shie Mannor, Nahum Shimkin
2018	A*	`conf`	Path Consistency Learning in Tsallis Entropy Regularized MDPs. ICML Yinlam Chow, Ofir Nachum, Mohammad Ghavamzadeh
2018	J	`jnl`	Path Consistency Learning in Tsallis Entropy Regularized MDPs. CoRR Ofir Nachum, Yinlam Chow, Mohammad Ghavamzadeh
2018	J	`jnl`	Proximal Gradient Temporal Difference Learning: Stable Reinforcement Learning with Polynomial Sample Complexity. J. Artif. Intell. Res. Bo Liu, Ian Gemp, Mohammad Ghavamzadeh, Ji Liu, Sridhar Mahadevan, Marek Petrik
2018	J	`jnl`	Risk-Sensitive Generative Adversarial Imitation Learning. CoRR Jonathan Lacotte, Yinlam Chow, Mohammad Ghavamzadeh, Marco Pavone
2018	A	`conf`	Robust Locally-Linear Controllable Embedding. AISTATS Ershad Banijamali, Rui Shu, Mohammad Ghavamzadeh, Hung Bui, Ali Ghodsi
2017	A*	`conf`	Active Learning for Accurate Estimation of Linear Models. ICML Carlos Riquelme, Mohammad Ghavamzadeh, Alessandro Lazaric
2017	J	`jnl`	Active Learning for Accurate Estimation of Linear Models. CoRR Carlos Riquelme, Mohammad Ghavamzadeh, Alessandro Lazaric
2017	A*	`conf`	Automated Data Cleansing through Meta-Learning. AAAI Ian Gemp, Georgios Theocharous, Mohammad Ghavamzadeh
2017	A*	`conf`	Bottleneck Conditional Density Estimation. ICML Rui Shu, Hung Hai Bui, Mohammad Ghavamzadeh
2017	—	`conf`	Conservative Contextual Linear Bandits. NIPS Abbas Kazerouni, Mohammad Ghavamzadeh, Yasin Abbasi, Benjamin Van Roy
2017	J	`jnl`	Diffusion Independent Semi-Bandit Influence Maximization. CoRR Sharan Vaswani, Branislav Kveton, Zheng Wen, Mohammad Ghavamzadeh, Laks V. S. Lakshmanan, Mark Schmidt
2017	J	`jnl`	Disentangling Dynamics and Content for Control and Planning. CoRR Ershad Banijamali, Ahmad Khajenezhad, Ali Ghodsi, Mohammad Ghavamzadeh
2017	—	`conf`	Importance of Recommendation Policy Space in Addressing Click Sparsity in Personalized Advertisement Display. MLDM Sougata Chaudhuri, Georgios Theocharous, Mohammad Ghavamzadeh
2017	A*	`conf`	Model-Independent Online Learning for Influence Maximization. ICML Sharan Vaswani, Branislav Kveton, Zheng Wen, Mohammad Ghavamzadeh, Laks V. S. Lakshmanan, Mark Schmidt
2017	A*	`conf`	Online Learning to Rank in Stochastic Click Models. ICML Masrour Zoghi, Tomás Tunys, Mohammad Ghavamzadeh, Branislav Kveton, Csaba Szepesvári, Zheng Wen
2017	J	`jnl`	Online Learning to Rank in Stochastic Click Models. CoRR Mohammad Ghavamzadeh, Branislav Kveton, Csaba Szepesvári, Tomás Tunys, Zheng Wen, Masrour Zoghi
2017	A*	`conf`	Predictive Off-Policy Policy Evaluation for Nonstationary Decision Problems, with Applications to Digital Marketing. AAAI Philip S. Thomas, Georgios Theocharous, Mohammad Ghavamzadeh, Ishan Durugkar, Emma Brunskill
2017	J	`jnl`	Risk-Constrained Reinforcement Learning with Percentile Risk Criteria. J. Mach. Learn. Res. Yinlam Chow, Mohammad Ghavamzadeh, Lucas Janson, Marco Pavone
2017	J	`jnl`	Robust Locally-Linear Controllable Embedding. CoRR Ershad Banijamali, Rui Shu, Mohammad Ghavamzadeh, Hung Bui, Ali Ghodsi
2017	J	`jnl`	Sequential Decision Making With Coherent Risk. IEEE Trans. Autom. Control. Aviv Tamar, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor
2017	A	`conf`	Sequential Multiple Hypothesis Testing with Type I Error Control. AISTATS Alan Malek, Sumeet Katariya, Yinlam Chow, Mohammad Ghavamzadeh
2016	J	`jnl`	Analysis of Classification-based Policy Iteration Algorithms. J. Mach. Learn. Res. Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos
2016	J	`jnl`	Bayesian Policy Gradient and Actor-Critic Algorithms. J. Mach. Learn. Res. Mohammad Ghavamzadeh, Yaakov Engel, Michal Valko
2016	J	`jnl`	Bayesian Reinforcement Learning: A Survey. CoRR Mohammad Ghavamzadeh, Shie Mannor, Joelle Pineau, Aviv Tamar
2016	J	`jnl`	Bottleneck Conditional Density Estimation. CoRR Rui Shu, Hung Hai Bui, Mohammad Ghavamzadeh
2016	J	`jnl`	Conservative Contextual Linear Bandits. CoRR Abbas Kazerouni, Mohammad Ghavamzadeh, Benjamin Van Roy
2016	—	`conf`	Graphical Model Sketch. ECML/PKDD (1) Branislav Kveton, Hung Bui, Mohammad Ghavamzadeh, Georgios Theocharous, S. Muthukrishnan, Siqi Sun
2016	J	`jnl`	Graphical Model Sketch. CoRR Branislav Kveton, Hung Bui, Mohammad Ghavamzadeh, Georgios Theocharous, S. Muthukrishnan, Siqi Sun
2016	A	`conf`	Improved Learning Complexity in Combinatorial Pure Exploration Bandits. AISTATS Victor Gabillon, Alessandro Lazaric, Mohammad Ghavamzadeh, Ronald Ortner, Peter L. Bartlett
2016	J	`jnl`	Personalized Advertisement Recommendation: A Ranking Approach to Address the Ubiquitous Click Sparsity Problem. CoRR Sougata Chaudhuri, Georgios Theocharous, Mohammad Ghavamzadeh
2016	A*	`conf`	Proximal Gradient Temporal Difference Learning Algorithms. IJCAI Bo Liu, Ji Liu, Mohammad Ghavamzadeh, Sridhar Mahadevan, Marek Petrik
2016	J	`jnl`	Regularized Policy Iteration with Nonparametric Function Spaces. J. Mach. Learn. Res. Amir-massoud Farahmand, Mohammad Ghavamzadeh, Csaba Szepesvári, Shie Mannor
2016	—	`conf`	Safe Policy Improvement by Minimizing Robust Baseline Regret. NIPS Mohammad Ghavamzadeh, Marek Petrik, Yinlam Chow
2016	J	`jnl`	Variance-constrained actor-critic algorithms for discounted and average reward MDPs. Mach. Learn. Prashanth L. A., Mohammad Ghavamzadeh
2015	—	`conf`	Ad Recommendation Systems for Life-Time Value Optimization. WWW (Companion Volume) Georgios Theocharous, Philip S. Thomas, Mohammad Ghavamzadeh
2015	J	`jnl`	Approximate modified policy iteration and its application to the game of Tetris. J. Mach. Learn. Res. Bruno Scherrer, Mohammad Ghavamzadeh, Victor Gabillon, Boris Lesner, Matthieu Geist
2015	J	`jnl`	Bayesian Reinforcement Learning: A Survey. Found. Trends Mach. Learn. Mohammad Ghavamzadeh, Shie Mannor, Joelle Pineau, Aviv Tamar
2015	J	`jnl`	Classification-Based Approximate Policy Iteration. IEEE Trans. Autom. Control. Amir-massoud Farahmand, Doina Precup, André da Motta Salles Barreto, Mohammad Ghavamzadeh
2015	A	`conf`	Finite-Sample Analysis of Proximal Gradient TD Algorithms. UAI Bo Liu, Ji Liu, Mohammad Ghavamzadeh, Sridhar Mahadevan, Marek Petrik
2015	A*	`conf`	High Confidence Policy Improvement. ICML Philip S. Thomas, Georgios Theocharous, Mohammad Ghavamzadeh
2015	A*	`conf`	High-Confidence Off-Policy Evaluation. AAAI Philip S. Thomas, Georgios Theocharous, Mohammad Ghavamzadeh
2015	A*	`conf`	Maximum Entropy Semi-Supervised Inverse Reinforcement Learning. IJCAI Julien Audiffren, Michal Valko, Alessandro Lazaric, Mohammad Ghavamzadeh
2015	A*	`conf`	Personalized Ad Recommendation Systems for Life-Time Value Optimization with Guarantees. IJCAI Georgios Theocharous, Philip S. Thomas, Mohammad Ghavamzadeh
2015	—	`conf`	Policy Gradient for Coherent Risk Measures. NIPS Aviv Tamar, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor
2015	J	`jnl`	Policy Gradient for Coherent Risk Measures. CoRR Aviv Tamar, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor
2015	J	`jnl`	Risk-Constrained Reinforcement Learning with Percentile Risk Criteria. CoRR Yinlam Chow, Mohammad Ghavamzadeh, Lucas Janson, Marco Pavone
2015	J	`jnl`	Upper-Confidence-Bound Algorithms for Active Learning in Multi-Armed Bandits. CoRR Alexandra Carpentier, Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos, Peter Auer, András Antos
2014	J	`jnl`	Actor-Critic Algorithms for Risk-Sensitive Reinforcement Learning. CoRR Prashanth L. A., Mohammad Ghavamzadeh
2014	—	`conf`	Algorithms for CVaR Optimization in MDPs. NIPS Yinlam Chow, Mohammad Ghavamzadeh
2014	J	`jnl`	Algorithms for CVaR Optimization in MDPs. CoRR Yinlam Chow, Mohammad Ghavamzadeh
2014	J	`jnl`	Classification-based Approximate Policy Iteration: Experiments and Extended Discussions. CoRR Amir-massoud Farahmand, Doina Precup, André da Motta Salles Barreto, Mohammad Ghavamzadeh
2013	—	`conf`	A Generalized Kernel Approach to Structured Output Learning. ICML (1) Hachem Kadri, Mohammad Ghavamzadeh, Philippe Preux
2013	—	`conf`	Actor-Critic Algorithms for Risk-Sensitive MDPs. NIPS Prashanth L. A., Mohammad Ghavamzadeh
2013	—	`conf`	Approximate Dynamic Programming Finally Performs Well in the Game of Tetris. NIPS Victor Gabillon, Mohammad Ghavamzadeh, Bruno Scherrer
2013	—	`conf`	Cost-sensitive Multiclass Classification Risk Bounds. ICML (3) Bernardo Ávila Pires, Csaba Szepesvári, Mohammad Ghavamzadeh
2012	A*	`conf`	A Dantzig Selector Approach to Temporal Difference Learning. ICML Matthieu Geist, Bruno Scherrer, Alessandro Lazaric, Mohammad Ghavamzadeh
2012	J	`jnl`	A Generalized Kernel Approach to Structured Output Learning CoRR Hachem Kadri, Mohammad Ghavamzadeh, Philippe Preux
2012	J	`jnl`	Approximate Modified Policy Iteration CoRR Bruno Scherrer, Victor Gabillon, Mohammad Ghavamzadeh, Matthieu Geist
2012	A*	`conf`	Approximate Modified Policy Iteration. ICML Bruno Scherrer, Victor Gabillon, Mohammad Ghavamzadeh, Matthieu Geist
2012	—	`ch.`	Bayesian Reinforcement Learning. Reinforcement Learning Nikos Vlassis, Mohammad Ghavamzadeh, Shie Mannor, Pascal Poupart
2012	—	`conf`	Best Arm Identification: A Unified Approach to Fixed Budget and Fixed Confidence. NIPS Victor Gabillon, Mohammad Ghavamzadeh, Alessandro Lazaric
2012	A*	`conf`	Conservative and Greedy Approaches to Classification-Based Policy Iteration. AAAI Mohammad Ghavamzadeh, Alessandro Lazaric
2012	J	`jnl`	Finite-sample analysis of least-squares policy iteration. J. Mach. Learn. Res. Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos
2012	—	`ch.`	Least-Squares Methods for Policy Iteration. Reinforcement Learning Lucian Busoniu, Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos, Robert Babuska, Bart De Schutter
2012	—	`conf`	Semi-Supervised Apprenticeship Learning. EWRL Michal Valko, Mohammad Ghavamzadeh, Alessandro Lazaric
2011	A*	`conf`	Classification-based Policy Iteration with a Critic. ICML Victor Gabillon, Alessandro Lazaric, Mohammad Ghavamzadeh, Bruno Scherrer
2011	A*	`conf`	Finite-Sample Analysis of Lasso-TD. ICML Mohammad Ghavamzadeh, Alessandro Lazaric, Rémi Munos, Matthew W. Hoffman
2011	—	`conf`	Multi-Bandit Best Arm Identification. NIPS Victor Gabillon, Mohammad Ghavamzadeh, Alessandro Lazaric, Sébastien Bubeck
2011	—	`conf`	Regularized Least Squares Temporal Difference Learning with Nested ℓ2 and ℓ1 Penalization. EWRL Matthew W. Hoffman, Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos
2011	—	`conf`	Speedy Q-Learning. NIPS Mohammad Gheshlaghi Azar, Rémi Munos, Mohammad Ghavamzadeh, Hilbert J. Kappen
2011	B	`conf`	Upper-Confidence-Bound Algorithms for Active Learning in Multi-armed Bandits. ALT Alexandra Carpentier, Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos, Peter Auer
2010	A*	`conf`	Analysis of a Classification-based Policy Iteration Algorithm. ICML Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos
2010	A*	`conf`	Bayesian Multi-Task Reinforcement Learning. ICML Alessandro Lazaric, Mohammad Ghavamzadeh
2010	A*	`conf`	Finite-Sample Analysis of LSTD. ICML Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos
2010	C	`conf`	Finite-sample Analysis of Bellman Residual Minimization. ACML Odalric-Ambrym Maillard, Rémi Munos, Alessandro Lazaric, Mohammad Ghavamzadeh
2010	—	`conf`	LSTD with Random Projections. NIPS Mohammad Ghavamzadeh, Alessandro Lazaric, Odalric-Ambrym Maillard, Rémi Munos
2009	J	`jnl`	Natural actor-critic algorithms. Autom. Shalabh Bhatnagar, Richard S. Sutton, Mohammad Ghavamzadeh, Mark Lee
2009	C	`conf`	Regularized Fitted Q-Iteration for planning in continuous-space Markovian decision problems. ACC Amir Massoud Farahmand, Mohammad Ghavamzadeh, Csaba Szepesvári, Shie Mannor
2008	—	`conf`	Regularized Fitted Q-Iteration: Application to Planning. EWRL Amir Massoud Farahmand, Mohammad Ghavamzadeh, Csaba Szepesvári, Shie Mannor
2008	—	`conf`	Regularized Policy Iteration. NIPS Amir Massoud Farahmand, Mohammad Ghavamzadeh, Csaba Szepesvári, Shie Mannor
2007	A*	`conf`	Bayesian actor-critic algorithms. ICML Mohammad Ghavamzadeh, Yaakov Engel
2007	J	`jnl`	Hierarchical Average Reward Reinforcement Learning. J. Mach. Learn. Res. Mohammad Ghavamzadeh, Sridhar Mahadevan
2007	—	`conf`	Incremental Natural Actor-Critic Algorithms. NIPS Shalabh Bhatnagar, Richard S. Sutton, Mohammad Ghavamzadeh, Mark Lee
2006	—	`conf`	Bayesian Policy Gradient Algorithms. NIPS Mohammad Ghavamzadeh, Yaakov Engel
2006	J	`jnl`	Hierarchical multi-agent reinforcement learning. Auton. Agents Multi Agent Syst. Mohammad Ghavamzadeh, Sridhar Mahadevan, Rajbala Makar
2005	J	`jnl`	The Workshop Program at the Nineteenth National Conference on Artificial Intelligence. AI Mag. Ion Muslea, Virginia Dignum, Daniel D. Corkill, Catholijn M. Jonker, Frank Dignum, Silvia Coradeschi, Alessandro Saffiotti, Dan Fu, Jeff Orkin, William Cheetham, Kai Goebel, Piero P. Bonissone, Leen-Kiat Soh, Randolph M. Jones, Robert E. Wray III, Matthias Scheutz, Daniela Pucci de Farias, Shie Mannor, Georgios Theocharous, Doina Precup, Bamshad Mobasher, Sarabjot S. Anand, Bettina Berendt, Andreas Hotho, Hans W. Guesgen, Michael T. Rosenstein, Mohammad Ghavamzadeh
2004	A	`conf`	Learning to Communicate and Act Using Hierarchical Reinforcement Learning. AAMAS Mohammad Ghavamzadeh, Sridhar Mahadevan
2003	A*	`conf`	Hierarchical Policy Gradient Algorithms. ICML Mohammad Ghavamzadeh, Sridhar Mahadevan
2002	A	`conf`	A multiagent reinforcement learning algorithm by dynamically merging markov decision processes. AAMAS Mohammad Ghavamzadeh, Sridhar Mahadevan
2002	A*	`conf`	Hierarchically Optimal Average Reward Reinforcement Learning. ICML Mohammad Ghavamzadeh, Sridhar Mahadevan
2001	A*	`conf`	Continuous-Time Hierarchical Reinforcement Learning. ICML Mohammad Ghavamzadeh, Sridhar Mahadevan
2001	—	`conf`	Hierarchical multi-agent reinforcement learning. Agents Rajbala Makar, Sridhar Mahadevan, Mohammad Ghavamzadeh