Mohammad Ghavamzadeh

ORCID

Publication Activity (10 Years)

Years Active: 2001-2024
Publications (10 Years): 152

Top Venues

Publications

Amin Rakhsha, Mete Kemertas, Mohammad Ghavamzadeh, Amir-massoud Farahmand
Maximum Entropy Model Correction in Reinforcement Learning. ICLR (2024)
Aldo Pacchiano, Mohammad Ghavamzadeh, Peter L. Bartlett
Contextual Bandits with Stage-wise Constraints. CoRR (2024)
Kyuyoung Kim, Jongheon Jeong, Minyong An, Mohammad Ghavamzadeh, Krishnamurthy Dj Dvijotham, Jinwoo Shin, Kimin Lee
Confidence-aware Reward Optimization for Fine-tuning Text-to-Image Models. ICLR (2024)
Kyuyoung Kim, Jongheon Jeong, Minyong An, Mohammad Ghavamzadeh, Krishnamurthy Dvijotham, Jinwoo Shin, Kimin Lee
Confidence-aware Reward Optimization for Fine-tuning Text-to-Image Models. CoRR (2024)
Ying Fan, Olivia Watkins, Yuqing Du, Hao Liu, Moonkyung Ryu, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Kangwook Lee, Kimin Lee
DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models. CoRR (2023)
Jia Lin Hau, Marek Petrik, Mohammad Ghavamzadeh
Entropic Risk Optimization in Discounted MDPs. AISTATS (2023)
Ying Fan, Olivia Watkins, Yuqing Du, Hao Liu, Moonkyung Ryu, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Kangwook Lee, Kimin Lee
Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models. NeurIPS (2023)
Jia Lin Hau, Erick Delage, Mohammad Ghavamzadeh, Marek Petrik
On Dynamic Program Decompositions of Static Risk Measures. CoRR (2023)
Christoph Dann, Mohammad Ghavamzadeh, Teodor V. Marinov
Multiple-policy High-confidence Policy Evaluation. AISTATS (2023)
Yinlam Chow, Aza Tulepbergenov, Ofir Nachum, Dhawal Gupta, Moonkyung Ryu, Mohammad Ghavamzadeh, Craig Boutilier
A Mixture-of-Expert Approach to RL-based Dialogue Management. ICLR (2023)
Dhawal Gupta, Yinlam Chow, Mohammad Ghavamzadeh, Craig Boutilier
Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management. CoRR (2023)
Jincheng Mei, Bo Dai, Alekh Agarwal, Mohammad Ghavamzadeh, Csaba Szepesvári, Dale Schuurmans
Ordering-based Conditions for Global Convergence of Policy Gradient Methods. NeurIPS (2023)
Jia Lin Hau, Erick Delage, Mohammad Ghavamzadeh, Marek Petrik
On Dynamic Programming Decompositions of Static Risk Measures in Markov Decision Processes. NeurIPS (2023)
Amin Rakhsha, Mete Kemertas, Mohammad Ghavamzadeh, Amir-massoud Farahmand
Maximum Entropy Model Correction in Reinforcement Learning. CoRR (2023)
Kishan Panaganti, Zaiyan Xu, Dileep M. Kalathil, Mohammad Ghavamzadeh
Bridging Distributionally Robust Learning and Offline RL: An Approach to Mitigate Distribution Shift and Partial Data Coverage. CoRR (2023)
Gecia Bravo-Hermsdorff, Róbert Busa-Fekete, Mohammad Ghavamzadeh, Andres Muñoz Medina, Umar Syed
Private and Communication-Efficient Algorithms for Entropy Estimation. CoRR (2023)
Joey Hong, Branislav Kveton, Manzil Zaheer, Sumeet Katariya, Mohammad Ghavamzadeh
Multi-Task Off-Policy Learning from Bandit Feedback. ICML (2023)
Erdem Biyik, Fan Yao, Yinlam Chow, Alex Haig, Chih-Wei Hsu, Mohammad Ghavamzadeh, Craig Boutilier
Preference Elicitation with Soft Attributes in Interactive Recommendation. CoRR (2023)
Mohammad Ghavamzadeh, Marek Petrik, Guy Tennenholtz
A Convex Relaxation Approach to Bayesian Regret Minimization in Offline Bandits. CoRR (2023)
Dhawal Gupta, Yinlam Chow, Azamat Tulepbergenov, Mohammad Ghavamzadeh, Craig Boutilier
Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management. NeurIPS (2023)
Mohammad Javad Azizi, Branislav Kveton, Mohammad Ghavamzadeh, Sumeet Katariya
Meta-Learning for Simple Regret Minimization. AAAI (2023)
Kimin Lee, Hao Liu, Moonkyung Ryu, Olivia Watkins, Yuqing Du, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Shixiang Shane Gu
Aligning Text-to-Image Models using Human Feedback. CoRR (2023)
Jihwan Jeong, Yinlam Chow, Guy Tennenholtz, Chih-Wei Hsu, Azamat Tulepbergenov, Mohammad Ghavamzadeh, Craig Boutilier
Factual and Personalized Recommendations using Language Models and Reinforcement Learning. CoRR (2023)
Moloud Abdar, Meenakshi Kollati, Swaraja Kuraparthi, Farhad Pourpanah, Daniel McDuff, Mohammad Ghavamzadeh, Shuicheng Yan, Abduallah Mohamed, Abbas Khosravi, Erik Cambria, Fatih Porikli
A Review of Deep Learning for Video Captioning. CoRR (2023)
Kishan Panaganti, Zaiyan Xu, Dileep Kalathil, Mohammad Ghavamzadeh
Distributionally Robust Behavioral Cloning for Robust Imitation Learning. CDC (2023)
Joey Hong, Branislav Kveton, Sumeet Katariya, Manzil Zaheer, Mohammad Ghavamzadeh
Multi-Task Off-Policy Learning from Bandit Feedback. CoRR (2022)
Amin Rakhsha, Andrew Wang, Mohammad Ghavamzadeh, Amir-massoud Farahmand
Operator Splitting Value Iteration. NeurIPS (2022)
Manan Tomar, Lior Shani, Yonathan Efroni, Mohammad Ghavamzadeh
Mirror Descent Policy Optimization. ICLR (2022)
Ahmadreza Moradipari, Mohammad Ghavamzadeh, Taha Rajabzadeh, Christos Thrampoulidis, Mahnoosh Alizadeh
Multi-Environment Meta-Learning in Stochastic Linear Bandits. ISIT (2022)
Ahmadreza Moradipari, Berkay Turan, Yasin Abbasi-Yadkori, Mahnoosh Alizadeh, Mohammad Ghavamzadeh
Feature and Parameter Selection in Stochastic Linear Bandits. ICML (2022)
Joey Hong, Branislav Kveton, Sumeet Katariya, Manzil Zaheer, Mohammad Ghavamzadeh
Deep Hierarchy in Bandits. CoRR (2022)
Gecia Bravo-Hermsdorff, Róbert Busa-Fekete, Mohammad Ghavamzadeh, Andrés Muñoz Medina, Umar Syed
Private and Communication-Efficient Algorithms for Entropy Estimation. NeurIPS (2022)
Joey Hong, Branislav Kveton, Manzil Zaheer, Mohammad Ghavamzadeh
Hierarchical Bayesian Bandits. AISTATS (2022)
Jorge A. Mendez, Alborz Geramifard, Mohammad Ghavamzadeh, Bing Liu
Reinforcement Learning of Multi-Domain Dialog Policies Via Action Embeddings. CoRR (2022)
Mohammad Javad Azizi, Branislav Kveton, Mohammad Ghavamzadeh, Sumeet Katariya
Meta-Learning for Simple Regret Minimization. CoRR (2022)
Jia Lin Hau, Marek Petrik, Mohammad Ghavamzadeh, Reazul Hasan Russel
RASR: Risk-Averse Soft-Robust MDPs with EVaR and Entropic Risk. CoRR (2022)
Kishan Panaganti, Zaiyan Xu, Dileep Kalathil, Mohammad Ghavamzadeh
Robust Reinforcement Learning using Offline Data. NeurIPS (2022)
Ido Greenberg, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor
Efficient Risk-Averse Reinforcement Learning. NeurIPS (2022)
Joey Hong, Branislav Kveton, Sumeet Katariya, Manzil Zaheer, Mohammad Ghavamzadeh
Deep Hierarchy in Bandits. ICML (2022)
Ahmadreza Moradipari, Mohammad Ghavamzadeh, Taha Rajabzadeh, Christos Thrampoulidis, Mahnoosh Alizadeh
Multi-Environment Meta-Learning in Stochastic Linear Bandits. CoRR (2022)
Ahmadreza Moradipari, Mohammad Ghavamzadeh, Mahnoosh Alizadeh
Collaborative Multi-agent Stochastic Linear Bandits. CoRR (2022)
Mohammad Javad Azizi, Branislav Kveton, Mohammad Ghavamzadeh
Fixed-Budget Best-Arm Identification in Structured Bandits. IJCAI (2022)
Amin Rakhsha, Andrew Wang, Mohammad Ghavamzadeh, Amir-massoud Farahmand
Operator Splitting Value Iteration. CoRR (2022)
Yinlam Chow, Aza Tulepbergenov, Ofir Nachum, Moonkyung Ryu, Mohammad Ghavamzadeh, Craig Boutilier
A Mixture-of-Expert Approach to RL-based Dialogue Management. CoRR (2022)
Ido Greenberg, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor
Efficient Risk-Averse Reinforcement Learning. CoRR (2022)
Kishan Panaganti, Zaiyan Xu, Dileep M. Kalathil, Mohammad Ghavamzadeh
Robust Reinforcement Learning using Offline Data. CoRR (2022)
Joey Hong, Branislav Kveton, Manzil Zaheer, Mohammad Ghavamzadeh, Craig Boutilier
Thompson Sampling with a Mixture Prior. AISTATS (2022)
Mohammad Javad Azizi, Thang Duong, Yasin Abbasi-Yadkori, András György, Claire Vernade, Mohammad Ghavamzadeh
Non-stationary Bandits and Meta-Learning with a Small Set of Optimal Arms. CoRR (2022)
Ahmadreza Moradipari, Mohammad Ghavamzadeh, Mahnoosh Alizadeh
Collaborative Multi-agent Stochastic Linear Bandits. ACC (2022)
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
A review of uncertainty quantification in deep learning: Techniques, applications and challenges. Inf. Fusion 76 (2021)
Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi
Adaptive Sampling for Minimax Fair Classification. CoRR (2021)
Mohammad Javad Azizi, Branislav Kveton, Mohammad Ghavamzadeh
Fixed-Budget Best-Arm Identification in Contextual Bandits: A Static-Adaptive Algorithm. CoRR (2021)
Aldo Pacchiano, Mohammad Ghavamzadeh, Peter L. Bartlett, Heinrich Jiang
Stochastic Bandits with Linear Constraints. AISTATS (2021)
Joey Hong, Branislav Kveton, Manzil Zaheer, Mohammad Ghavamzadeh, Craig Boutilier
Thompson Sampling with a Mixture Prior. CoRR (2021)
Amir Massoud Farahmand, Mohammad Ghavamzadeh
PID Accelerated Value Iteration Algorithm. ICML (2021)
Ahmadreza Moradipari, Yasin Abbasi-Yadkori, Mahnoosh Alizadeh, Mohammad Ghavamzadeh
Parameter and Feature Selection in Stochastic Linear Bandits. CoRR (2021)
Arash Mehrjou, Mohammad Ghavamzadeh, Bernhard Schölkopf
Neural Lyapunov Redesign. L4DC (2021)
Brandon Cui, Yinlam Chow, Mohammad Ghavamzadeh
Control-Aware Representations for Model-based Reinforcement Learning. ICLR (2021)
Shubhanshu Shekhar, Greg Fields, Mohammad Ghavamzadeh, Tara Javidi
Adaptive Sampling for Minimax Fair Classification. NeurIPS (2021)
Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi
Active Learning for Classification With Abstention. IEEE J. Sel. Areas Inf. Theory 2 (2) (2021)
Joey Hong, Branislav Kveton, Manzil Zaheer, Mohammad Ghavamzadeh
Hierarchical Bayesian Bandits. CoRR (2021)
Ravi Tej Akella, Kamyar Azizzadenesheli, Mohammad Ghavamzadeh, Animashree Anandkumar, Yisong Yue
Deep Bayesian Quadrature Policy Optimization. AAAI (2021)
Yinlam Chow, Brandon Cui, Moonkyung Ryu, Mohammad Ghavamzadeh
Variational Model-based Policy Optimization. IJCAI (2021)
Rui Shu, Tung Nguyen, Yinlam Chow, Tuan Pham, Khoat Than, Mohammad Ghavamzadeh, Stefano Ermon, Hung H. Bui
Predictive Coding for Locally-Linear Control. ICML (2020)
Rui Shu, Tung Nguyen, Yinlam Chow, Tuan Pham, Khoat Than, Mohammad Ghavamzadeh, Stefano Ermon, Hung H. Bui
Predictive Coding for Locally-Linear Control. CoRR (2020)
Daoming Lyu, Qi Qi, Mohammad Ghavamzadeh, Hengshuai Yao, Tianbao Yang, Bo Liu
Variance-Reduced Off-Policy Memory-Efficient Policy Search. CoRR (2020)
Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed, Mohammad Ghavamzadeh, Craig Boutilier
Non-Stationary Latent Bandits. CoRR (2020)
Evrard Garcelon, Mohammad Ghavamzadeh, Alessandro Lazaric, Matteo Pirotta
Improved Algorithms for Conservative Exploration in Bandits. AAAI (2020)
Evrard Garcelon, Mohammad Ghavamzadeh, Alessandro Lazaric, Matteo Pirotta
Conservative Exploration in Reinforcement Learning. CoRR (2020)
Jean Tarbouriech, Shubhanshu Shekhar, Matteo Pirotta, Mohammad Ghavamzadeh, Alessandro Lazaric
Active Model Estimation in Markov Decision Processes. CoRR (2020)
Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi
Active Learning for Classification with Abstention. ISIT (2020)
Yonathan Efroni, Mohammad Ghavamzadeh, Shie Mannor
Online Planning with Lookahead Policies. NeurIPS (2020)
Manan Tomar, Lior Shani, Yonathan Efroni, Mohammad Ghavamzadeh
Mirror Descent Policy Optimization. CoRR (2020)
Arash Mehrjou, Mohammad Ghavamzadeh, Bernhard Schölkopf
Automatic Policy Synthesis to Improve the Safety of Nonlinear Dynamical Systems. CoRR (2020)
Aldo Pacchiano, Mohammad Ghavamzadeh, Peter L. Bartlett, Heinrich Jiang
Stochastic Bandits with Linear Constraints. CoRR (2020)
Manan Tomar, Yonathan Efroni, Mohammad Ghavamzadeh
Multi-step Greedy Reinforcement Learning Algorithms. ICML (2020)
Elita A. Lobo, Mohammad Ghavamzadeh, Marek Petrik
Soft-Robust Algorithms for Handling Model Misspecification. CoRR (2020)
Ravi Tej Akella, Kamyar Azizzadenesheli, Mohammad Ghavamzadeh, Anima Anandkumar, Yisong Yue
Deep Bayesian Quadrature Policy Optimization. CoRR (2020)
Romina Abachi, Mohammad Ghavamzadeh, Amir-massoud Farahmand
Policy-Aware Model Learning for Policy Gradient Methods. CoRR (2020)
Shubhanshu Shekhar, Tara Javidi, Mohammad Ghavamzadeh
Adaptive Sampling for Estimating Probability Distributions. ICML (2020)
Branislav Kveton, Manzil Zaheer, Csaba Szepesvári, Lihong Li, Mohammad Ghavamzadeh, Craig Boutilier
Randomized Exploration in Generalized Linear Bandits. AISTATS (2020)
Evrard Garcelon, Mohammad Ghavamzadeh, Alessandro Lazaric, Matteo Pirotta
Improved Algorithms for Conservative Exploration in Bandits. CoRR (2020)
Bo Liu, Ji Liu, Mohammad Ghavamzadeh, Sridhar Mahadevan, Marek Petrik
Finite-Sample Analysis of GTD Algorithms. CoRR (2020)
Evrard Garcelon, Mohammad Ghavamzadeh, Alessandro Lazaric, Matteo Pirotta
Conservative Exploration in Reinforcement Learning. AISTATS (2020)
Brandon Cui, Yinlam Chow, Mohammad Ghavamzadeh
Control-Aware Representations for Model-based Reinforcement Learning. CoRR (2020)
Bo Liu, Ian Gemp, Mohammad Ghavamzadeh, Ji Liu, Sridhar Mahadevan, Marek Petrik
Proximal Gradient Temporal Difference Learning: Stable Reinforcement Learning with Polynomial Sample Complexity. CoRR (2020)
Nir Levine, Yinlam Chow, Rui Shu, Ang Li, Mohammad Ghavamzadeh, Hung Bui
Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control. ICLR (2020)
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
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges. CoRR (2020)
Jean Tarbouriech, Shubhanshu Shekhar, Matteo Pirotta, Mohammad Ghavamzadeh, Alessandro Lazaric
Active Model Estimation in Markov Decision Processes. UAI (2020)
Yinlam Chow, Brandon Cui, Moonkyung Ryu, Mohammad Ghavamzadeh
Variational Model-based Policy Optimization. CoRR (2020)
Yinlam Chow, Ofir Nachum, Aleksandra Faust, Edgar A. Duéñez-Guzmán, Mohammad Ghavamzadeh
Safe Policy Learning for Continuous Control. CoRL (2020)
Branislav Kveton, Csaba Szepesvári, Mohammad Ghavamzadeh, Craig Boutilier
Perturbed-History Exploration in Stochastic Linear Bandits. CoRR (2019)
Ershad Banijamali, Yasin Abbasi-Yadkori, Mohammad Ghavamzadeh, Nikos Vlassis
Optimizing over a Restricted Policy Class in MDPs. AISTATS (2019)
Yinlam Chow, Ofir Nachum, Aleksandra Faust, Mohammad Ghavamzadeh, Edgar A. Duéñez-Guzmán
Lyapunov-based Safe Policy Optimization for Continuous Control. CoRR (2019)
Branislav Kveton, Csaba Szepesvári, Mohammad Ghavamzadeh, Craig Boutilier
Perturbed-History Exploration in Stochastic Linear Bandits. UAI (2019)
Yonathan Efroni, Nadav Merlis, Mohammad Ghavamzadeh, Shie Mannor
Tight Regret Bounds for Model-Based Reinforcement Learning with Greedy Policies. CoRR (2019)
Scott Fujimoto, Edoardo Conti, Mohammad Ghavamzadeh, Joelle Pineau
Benchmarking Batch Deep Reinforcement Learning Algorithms. CoRR (2019)
Manan Tomar, Yonathan Efroni, Mohammad Ghavamzadeh
Multi-step Greedy Policies in Model-Free Deep Reinforcement Learning. CoRR (2019)
Yonathan Efroni, Mohammad Ghavamzadeh, Shie Mannor
Multi-Step Greedy and Approximate Real Time Dynamic Programming. CoRR (2019)
Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi
Binary Classification with Bounded Abstention Rate. CoRR (2019)

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Publication Activity (10 Years)

Top Topics

Top Venues

Mohammad Ghavamzadeh