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Mohammad Ghavamzadeh

Adaptive Sampling for Minimax Fair Classification


Mar 01, 2021
Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi

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* 29 pages, 6 figures 
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Non-Stationary Latent Bandits


Dec 01, 2020
Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed, Mohammad Ghavamzadeh, Craig Boutilier

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* 15 pages, 4 figures 
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Soft-Robust Algorithms for Handling Model Misspecification


Nov 30, 2020
Elita A. Lobo, Mohammad Ghavamzadeh, Marek Petrik

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A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges


Nov 17, 2020
Moloud Abdar, Farhad Pourpanah, Sadiq Hussain, Dana Rezazadegan, Li Liu, Mohammad Ghavamzadeh, Paul Fieguth, Xiaochun Cao, Abbas Khosravi, U Rajendra Acharya, Vladimir Makarenkov, Saeid Nahavandi

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Variance-Reduced Off-Policy Memory-Efficient Policy Search


Sep 14, 2020
Daoming Lyu, Qi Qi, Mohammad Ghavamzadeh, Hengshuai Yao, Tianbao Yang, Bo Liu

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Finite-Sample Analysis of Proximal Gradient TD Algorithms


Jul 03, 2020
Bo Liu, Ji Liu, Mohammad Ghavamzadeh, Sridhar Mahadevan, Marek Petrik

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* 31st Conference on Uncertainty in Artificial Intelligence (UAI). arXiv admin note: substantial text overlap with arXiv:2006.03976 
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Deep Bayesian Quadrature Policy Optimization


Jun 28, 2020
Akella Ravi Tej, Kamyar Azizzadenesheli, Mohammad Ghavamzadeh, Anima Anandkumar, Yisong Yue

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* Code available at https://github.com/Akella17/Deep-Bayesian-Quadrature-Policy-Optimization 
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Variational Model-based Policy Optimization


Jun 24, 2020
Yinlam Chow, Brandon Cui, MoonKyung Ryu, Mohammad Ghavamzadeh

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Control-Aware Representations for Model-based Reinforcement Learning


Jun 24, 2020
Brandon Cui, Yinlam Chow, Mohammad Ghavamzadeh

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Stochastic Bandits with Linear Constraints


Jun 17, 2020
Aldo Pacchiano, Mohammad Ghavamzadeh, Peter Bartlett, Heinrich Jiang

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* 9 pages 
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Mirror Descent Policy Optimization


Jun 09, 2020
Manan Tomar, Lior Shani, Yonathan Efroni, Mohammad Ghavamzadeh

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Proximal Gradient Temporal Difference Learning: Stable Reinforcement Learning with Polynomial Sample Complexity


Jun 06, 2020
Bo Liu, Ian Gemp, Mohammad Ghavamzadeh, Ji Liu, Sridhar Mahadevan, Marek Petrik

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* Journal of Artificial Intelligence (JAIR) 
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Finite-Sample Analysis of GTD Algorithms


Jun 06, 2020
Bo Liu, Ji Liu, Mohammad Ghavamzadeh, Sridhar Mahadevan, Marek Petrik

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* 31st Conference on Uncertainty in Artificial Intelligence (UAI). arXiv admin note: substantial text overlap with arXiv:2006.03976 
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Automatic Policy Synthesis to Improve the Safety of Nonlinear Dynamical Systems


Jun 06, 2020
Arash Mehrjou, Mohammad Ghavamzadeh, Bernhard Schölkopf

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* 24 pages 
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Active Model Estimation in Markov Decision Processes


Mar 06, 2020
Jean Tarbouriech, Shubhanshu Shekhar, Matteo Pirotta, Mohammad Ghavamzadeh, Alessandro Lazaric

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Predictive Coding for Locally-Linear Control


Mar 02, 2020
Rui Shu, Tung Nguyen, Yinlam Chow, Tuan Pham, Khoat Than, Mohammad Ghavamzadeh, Stefano Ermon, Hung H. Bui

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Policy-Aware Model Learning for Policy Gradient Methods


Feb 28, 2020
Romina Abachi, Mohammad Ghavamzadeh, Amir-massoud Farahmand

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Improved Algorithms for Conservative Exploration in Bandits


Feb 08, 2020
Evrard Garcelon, Mohammad Ghavamzadeh, Alessandro Lazaric, Matteo Pirotta

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Conservative Exploration in Reinforcement Learning


Feb 08, 2020
Evrard Garcelon, Mohammad Ghavamzadeh, Alessandro Lazaric, Matteo Pirotta

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Adaptive Sampling for Estimating Multiple Probability Distributions


Dec 07, 2019
Shubhanshu Shekhar, Tara Javidi, Mohammad Ghavamzadeh

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* 40 pages, 3 figures 
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Multi-step Greedy Policies in Model-Free Deep Reinforcement Learning


Oct 14, 2019
Manan Tomar, Yonathan Efroni, Mohammad Ghavamzadeh

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Benchmarking Batch Deep Reinforcement Learning Algorithms


Oct 03, 2019
Scott Fujimoto, Edoardo Conti, Mohammad Ghavamzadeh, Joelle Pineau

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* Deep RL Workshop NeurIPS 2019 
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Multi-Step Greedy and Approximate Real Time Dynamic Programming


Sep 10, 2019
Yonathan Efroni, Mohammad Ghavamzadeh, Shie Mannor

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Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control


Sep 04, 2019
Nir Levine, Yinlam Chow, Rui Shu, Ang Li, Mohammad Ghavamzadeh, Hung Bui

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