M. Ghavamzadeh

Sridhar Mahadevan, Mohammad Ghavamzadeh, M. Ghavamzadeh, 2004, Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, 2004. AAMAS 2004..

Active Learning for Binary Classification with Abstention pdf

Tara Javidi, Mohammad Ghavamzadeh, Shubhanshu Shekhar, 2019, ArXiv.

Ad Recommendation Systems for Life-Time Value Optimization

Philip S. Thomas, Mohammad Ghavamzadeh, Georgios Theocharous, 2015, WWW.

Bottleneck Conditional Density Estimation

Mohammad Ghavamzadeh, Hung Hai Bui, Rui Shu, 2016, ICML.

Graphical Model Sketch

S. Muthukrishnan, Mohammad Ghavamzadeh, Branislav Kveton, 2016, ECML/PKDD.

Active Learning for Accurate Estimation of Linear Models

Alessandro Lazaric, Carlos Riquelme, Mohammad Ghavamzadeh, 2017, ICML.

Algorithms for CVaR Optimization in MDPs

Mohammad Ghavamzadeh, Yinlam Chow, M. Ghavamzadeh, 2014, NIPS.

Sequential Multiple Hypothesis Testing with Type I Error Control

Alan Malek, Mohammad Ghavamzadeh, Yinlam Chow, 2017, AISTATS.

Hierarchical multi-agent reinforcement learning

Sridhar Mahadevan, Mohammad Ghavamzadeh, Rajbala Makar, 2001, AGENTS '01.

Upper-Confidence-Bound Algorithms for Active Learning in Multi-Armed Bandits

Alessandro Lazaric, Alexandra Carpentier, Mohammad Ghavamzadeh, 2011, ALT.

Finite-sample analysis of least-squares policy iteration

Alessandro Lazaric, Rémi Munos, Mohammad Ghavamzadeh, 2012, J. Mach. Learn. Res..

Predictive Off-Policy Policy Evaluation for Nonstationary Decision Problems, with Applications to Digital Marketing

Philip S. Thomas, Mohammad Ghavamzadeh, Georgios Theocharous, 2017, AAAI.

Classification-based Approximate Policy Iteration: Experiments and Extended Discussions pdf

André da Motta Salles Barreto, Doina Precup, Mohammad Ghavamzadeh, 2014, ArXiv.

Risk-Constrained Reinforcement Learning with Percentile Risk Criteria pdf

Marco Pavone, Lucas Janson, Mohammad Ghavamzadeh, 2015, J. Mach. Learn. Res..

Regularized Fitted Q-iteration : Application to Bounded Resource Planning

Csaba Szepesvari, Shie Mannor, A. Farahmand, 2009 .

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

Li Liu, Xiaochun Cao, Abbas Khosravi, 2020, Inf. Fusion.

Natural Actor – Crit ic Algorithms

R. Sutton, S. Bhatnagar, M. Ghavamzadeh, 2009 .

Natural-Gradient Actor-Critic Algorithms

R. Sutton, S. Bhatnagar, M. Ghavamzadeh, 2007 .

12-009 Least-squares methods for policy iteration ∗

L. Buşoniu, A. Lazaric, M. Ghavamzadeh, 2016 .

Hierarchical Average Reward Reinforcement Learning Hierarchical Average Reward Reinforcement Learning

M. Ghavamzadeh, S. Mahadevan, 2007 .

Semi-Supervised Inverse Reinforcement Learning

A. Lazaric, M. Ghavamzadeh, Michal Valko, 2012 .

Multi-Step Greedy and Approximate Real Time Dynamic Programming pdf

Shie Mannor, Mohammad Ghavamzadeh, Yonathan Efroni, 2019, ArXiv.

Nav RNav G Nav Y Root Cooperative Subtask Communicate Not −

M. Ghavamzadeh, S. Mahadevan, 2022 .

Robust Locally-Linear Controllable Embedding

Ali Ghodsi, Ershad Banijamali, Mohammad Ghavamzadeh, 2017, AISTATS.

Analysis of Classication-bas ed Policy Iteration Algorithms

A. Lazaric, M. Ghavamzadeh, R. emiMunos, 2016 .

Speedy q-learning: a computationally efficient reinforcement learning algorithm with a near optimal rate of convergence

H. Kappen, R. Munos, M. Ghavamzadeh, 2013 .

Regularized Policy Iteration

Shie Mannor, Csaba Szepesvári, Mohammad Ghavamzadeh, 2008, NIPS.

Online Learning to Rank in Stochastic Click Models

Csaba Szepesvári, Masrour Zoghi, Branislav Kveton, 2017, ICML.

Hierarchical Hybrid Reinforcement Learning Algorithms

M. Ghavamzadeh, 2009 .

Proceedings of the Nineteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2016

Peter L. Bartlett, Alessandro Lazaric, Ronald Ortner, 2016 .

Sequential Decision Making With Coherent Risk

Shie Mannor, Mohammad Ghavamzadeh, Aviv Tamar, 2017, IEEE Transactions on Automatic Control.

Efficient Risk-Averse Reinforcement Learning

Shie Mannor, M. Ghavamzadeh, Yinlam Chow, 2022, 2205.05138.

Hierarchical multi-agent reinforcement learning

M. Ghavamzadeh, S. Mahadevan, R. Makar, 2001, Agents.

A Mixture-of-Expert Approach to RL-based Dialogue Management

M. Ghavamzadeh, Craig Boutilier, Ofir Nachum, 2022, International Conference on Learning Representations.

Non-stationary Bandits and Meta-Learning with a Small Set of Optimal Arms

M. J. Azizi, M. Ghavamzadeh, Yasin Abbasi-Yadkori, 2022, ArXiv.

Hierarchical reinforcement learning in continuous state and multi-agent environments

M. Ghavamzadeh, S. Mahadevan, 2005 .

Multi-Environment Meta-Learning in Stochastic Linear Bandits

M. Ghavamzadeh, M. Alizadeh, Christos Thrampoulidis, 2022, International Symposium on Information Theory.

Feature and Parameter Selection in Stochastic Linear Bandits

M. Ghavamzadeh, Yasin Abbasi-Yadkori, M. Alizadeh, 2021, ICML.

Collaborative Multi-agent Stochastic Linear Bandits

M. Ghavamzadeh, M. Alizadeh, Ahmadreza Moradipari, 2022, 2022 American Control Conference (ACC).

Parameter and Feature Selection in Stochastic Linear Bandits

M. Ghavamzadeh, Yasin Abbasi-Yadkori, M. Alizadeh, 2021, ArXiv.

An Experimental Evaluation of Reinforcement Learning for Gain Scheduling

Eric Moulines, Olivier Teytaud, Alessandra Russo, 2003, HIS.

Natural actorcritic algorithms.

Shalabh Bhatnagar, Richard S. Sutton, Mohammad Ghavamzadeh, 2009 .

A Mixture-of-Expert Approach to RL-based Dialogue Management

M. Ghavamzadeh, Craig Boutilier, Ofir Nachum, 2022, ICLR.

Robust Reinforcement Learning using Offline Data

M. Ghavamzadeh, D. Kalathil, Kishan Panaganti, 2022, ArXiv.

Non-stationary Bandits and Meta-Learning with a Small Set of Optimal Arms

M. J. Azizi, M. Ghavamzadeh, Yasin Abbasi-Yadkori, 2022, ArXiv.

Non-stationary Bandits and Meta-Learning with a Small Set of Optimal Arms

M. J. Azizi, M. Ghavamzadeh, Yasin Abbasi-Yadkori, 2022, ArXiv.

Robust Reinforcement Learning using Offline Data

M. Ghavamzadeh, D. Kalathil, Kishan Panaganti, 2022, Neural Information Processing Systems.

Actor-Critic Algorithms for Risk-Sensitive Reinforcement Learning

M. Ghavamzadeh, A. PrashanthL., Prashanth L, 2014, ArXiv.

Operator Splitting Value Iteration

M. Ghavamzadeh, Amir-massoud Farahmand, Amin Rakhsha, 2022, NeurIPS.

Dec . 13 , 2019 Safety and Robustness in Decision-making

Shie Mannor, M. Ghavamzadeh, Yisong Yue, 2022 .

Safe Policy Learning for Continuous Control

Aleksandra Faust, Ofir Nachum, Yinlam Chow, 2019, CoRL.

Efficient Risk-Averse Reinforcement Learning

Shie Mannor, M. Ghavamzadeh, Yinlam Chow, 2022, NeurIPS.

Multi-Task Off-Policy Learning from Bandit Feedback

B. Kveton, M. Zaheer, M. Ghavamzadeh, 2022, ICML.

11 Hierarchical Approaches to Concurrency , Multiagency , and Partial Observability

M. Ghavamzadeh, S. Mahadevan, Georgios Theocharous, 2004 .

Extending Hierarchical Reinforcement Learning to Continuous-Time, Average-Reward, and Multi-Agent Models

Sridhar Mahadevan, Mohammad Ghavamzadeh, Rajbala Makar, 2003 .

Online Planning with Lookahead Policies

Shie Mannor, M. Ghavamzadeh, Yonathan Efroni, 2020, NeurIPS.

Policy-Aware Model Learning for Policy Gradient Methods

M. Ghavamzadeh, Amir-massoud Farahmand, Romina Abachi, 2020, ArXiv.

Lyapunov-based Safe Policy Optimization for Continuous Control pdf

Mohammad Ghavamzadeh, Aleksandra Faust, Ofir Nachum, 2019, ArXiv.

Semi-Supervised Apprenticeship Learning

Alessandro Lazaric, Michal Valko, Mohammad Ghavamzadeh, 2012, EWRL.

Variational Model-based Policy Optimization pdf

Yinlam Chow, Mohammad Ghavamzadeh, Brandon Cui, 2020, IJCAI.

Natural actor-critic algorithms

Shalabh Bhatnagar, Mark Lee, Richard S. Sutton, 2009, Autom..

Fixed-Budget Best-Arm Identification in Contextual Bandits: A Static-Adaptive Algorithm

B. Kveton, M. Ghavamzadeh, Javad Azizi, 2021, ArXiv.

Aligning Text-to-Image Models using Human Feedback

P. Abbeel, S. Gu, M. Ghavamzadeh, 2023, ArXiv.

Predictive Coding for Locally-Linear Control

Stefano Ermon, Yinlam Chow, Mohammad Ghavamzadeh, 2020, ICML.

Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management

M. Ghavamzadeh, Craig Boutilier, Yinlam Chow, 2023, ArXiv.

A Review of Deep Learning for Video Captioning

Daniel J. McDuff, Abduallah A. Mohamed, M. Ghavamzadeh, 2023, ArXiv.

Adaptive Sampling for Minimax Fair Classification pdf

Tara Javidi, Mohammad Ghavamzadeh, Shubhanshu Shekhar, 2021, NeurIPS.

Optimizing over a Restricted Policy Class in MDPs

Yasin Abbasi-Yadkori, Ershad Banijamali, Nikos Vlassis, 2019, AISTATS.

Path Consistency Learning in Tsallis Entropy Regularized MDPs pdf

Ofir Nachum, Yinlam Chow, Mohammad Ghavamzadeh, 2018, ICML.

Variance-constrained actor-critic algorithms for discounted and average reward MDPs

Mohammad Ghavamzadeh, A. PrashanthL., M. Ghavamzadeh, 2014, Machine Learning.

More Robust Doubly Robust Off-policy Evaluation

Mehrdad Farajtabar, Mohammad Ghavamzadeh, Yinlam Chow, 2018, ICML.

Private and Communication-Efficient Algorithms for Entropy Estimation

Andrés Muñoz Medina, M. Ghavamzadeh, R. Busa-Fekete, 2023, NeurIPS.

Mirror Descent Policy Optimization

M. Ghavamzadeh, Yonathan Efroni, Manan Tomar, 2020, ICLR.

High Confidence Policy Improvement

Philip S. Thomas, Mohammad Ghavamzadeh, Georgios Theocharous, 2015, ICML.

Deep Bayesian Quadrature Policy Optimization pdf

Kamyar Azizzadenesheli, Yisong Yue, Anima Anandkumar, 2020, AAAI.

DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models

P. Abbeel, M. Ghavamzadeh, Craig Boutilier, 2023, ArXiv.

Continuous-Time Hierarchical Reinforcement Learning

Sridhar Mahadevan, Mohammad Ghavamzadeh, M. Ghavamzadeh, 2001, ICML.

Importance of Recommendation Policy Space in Addressing Click Sparsity in Personalized Advertisement Display

Mohammad Ghavamzadeh, Georgios Theocharous, Sougata Chaudhuri, 2017, MLDM.

Personalized Advertisement Recommendation: A Ranking Approach to Address the Ubiquitous Click Sparsity Problem pdf

Mohammad Ghavamzadeh, Georgios Theocharous, Sougata Chaudhuri, 2016, ArXiv.

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

M. Ghavamzadeh, Rui Shu, Yinlam Chow, 2019, ICLR.

Fixed-Budget Best-Arm Identification in Structured Bandits

B. Kveton, M. Ghavamzadeh, Javad Azizi, 2021, IJCAI.

Multi-step Greedy Reinforcement Learning Algorithms

M. Ghavamzadeh, Yonathan Efroni, Manan Tomar, 2019, ICML.

Policy Gradient for Coherent Risk Measures

Shie Mannor, Mohammad Ghavamzadeh, Aviv Tamar, 2015, NIPS.

A Block Coordinate Ascent Algorithm for Mean-Variance Optimization

Bo Liu, Yangyang Xu, Yinlam Chow, 2018, NeurIPS.

Risk-Sensitive Generative Adversarial Imitation Learning pdf

Marco Pavone, Jonathan Lacotte, Yinlam Chow, 2018, AISTATS.

Conservative Exploration in Reinforcement Learning

A. Lazaric, M. Ghavamzadeh, Matteo Pirotta, 2020, AISTATS.

Conservative Contextual Linear Bandits

Benjamin Van Roy, Mohammad Ghavamzadeh, Abbas Kazerouni, 2016, NIPS.

Benchmarking Batch Deep Reinforcement Learning Algorithms pdf

Joelle Pineau, Mohammad Ghavamzadeh, Scott Fujimoto, 2019, ArXiv.

Garbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits pdf

Tor Lattimore, Branislav Kveton, Mohammad Ghavamzadeh, 2018, ICML.

A Convex Relaxation Approach to Bayesian Regret Minimization in Offline Bandits

M. Ghavamzadeh, Marek Petrik, Guy Tennenholtz, 2023, ArXiv.

Meta-Learning for Simple Regret Minimization

B. Kveton, M. Ghavamzadeh, S. Katariya, 2022, AAAI.

Fixed-Budget Best-Arm Identification in Structured Bandits pdf

Mohammad Ghavamzadeh, Branislav Kveton, MohammadJavad Azizi, 2021, IJCAI.

Bayesian Multi-Task Reinforcement Learning

Alessandro Lazaric, Mohammad Ghavamzadeh, A. Lazaric, 2010, ICML.

Regularized Fitted Q-iteration: Application to Planning

Shie Mannor, Csaba Szepesvári, Mohammad Ghavamzadeh, 2008, EWRL.

Proximal Gradient Temporal Difference Learning Algorithms

Marek Petrik, Bo Liu, Ji Liu, 2016, IJCAI.

A Dantzig Selector Approach to Temporal Difference Learning

Matthieu Geist, Bruno Scherrer, Alessandro Lazaric, 2012, ICML.

Stochastic Bandits with Linear Constraints pdf

Mohammad Ghavamzadeh, Aldo Pacchiano, Heinrich Jiang, 2020, AISTATS.

On Dynamic Programming Decompositions of Static Risk Measures in Markov Decision Processes

M. Ghavamzadeh, Marek Petrik, E. Delage, 2023, 2304.12477.

Soft-Robust Algorithms for Handling Model Misspecification pdf

Mohammad Ghavamzadeh, Marek Petrik, Elita A. Lobo, 2020, ArXiv.

Entropic Risk Optimization in Discounted MDPs

M. Ghavamzadeh, Marek Petrik, J. Hau, 2023, AISTATS.

Safe Policy Improvement by Minimizing Robust Baseline Regret

Marek Petrik, Mohammad Ghavamzadeh, Yinlam Chow, 2016, NIPS.

Hierarchical Bayesian Bandits

B. Kveton, M. Zaheer, M. Ghavamzadeh, 2021, AISTATS.

Adaptive Sampling for Estimating Probability Distributions

Tara Javidi, Mohammad Ghavamzadeh, Shubhanshu Shekhar, 2020, ICML.

Adaptive Sampling for Estimating Multiple Probability Distributions

M. Ghavamzadeh, T. Javidi, S. Shekhar, 2019, ArXiv.

PID Accelerated Value Iteration Algorithm

Mohammad Ghavamzadeh, Amir Massoud Farahmand, A. Farahmand, 2021, ICML.

Bayesian Policy Gradient

M. Ghavamzadeh, Y. Engel, 2022 .

Learning to Communicate and Act in Cooperative Multiagent Systems using Hierarchical Reinforcement Learning

Sridhar Mahadevan, Mohammad Ghavamzadeh, M. Ghavamzadeh, 2004 .

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

Marek Petrik, Ji Liu, Bo Liu, 2018, J. Artif. Intell. Res..

Finite-Sample Analysis of GTD Algorithms pdf

Bo Liu, Ji Liu, Sridhar Mahadevan, 2020, ArXiv.

Deep Hierarchy in Bandits

B. Kveton, M. Zaheer, M. Ghavamzadeh, 2022, ICML.

Active Learning for Classification with Abstention

Tara Javidi, Mohammad Ghavamzadeh, Shubhanshu Shekhar, 2020, 2020 IEEE International Symposium on Information Theory (ISIT).

Model-Independent Online Learning for Influence Maximization

Laks V. S. Lakshmanan, Zheng Wen, Mark W. Schmidt, 2017, ICML.

Approximate Modified Policy Iteration pdf

Matthieu Geist, Bruno Scherrer, Mohammad Ghavamzadeh, 2012, ICML.

Variance-constrained actor-critic algorithms for discounted and average reward MDPs

L. A. Prashanth, M. Ghavamzadeh, 2016, Machine Learning.

Hierarchically Optimal Average Reward Reinforcement Learning

Sridhar Mahadevan, Mohammad Ghavamzadeh, M. Ghavamzadeh, 2002, ICML.

Learning to Cooperate using Hierarchical Reinforcement Learning

Sridhar Mahadevan, Mohammad Ghavamzadeh, M. Ghavamzadeh, 2006 .

RASR: Risk-Averse Soft-Robust MDPs with EVaR and Entropic Risk

M. Ghavamzadeh, Marek Petrik, R. Russel, 2022, arXiv.org.

Regularized Least Squares Temporal Difference Learning with Nested ℓ2 and ℓ1 Penalization

Matthew W. Hoffman, Alessandro Lazaric, Rémi Munos, 2011, EWRL.

Bayesian Reinforcement Learning

Shie Mannor, M. Ghavamzadeh, N. Vlassis, 2010, Encyclopedia of Machine Learning.

Control-Aware Representations for Model-based Reinforcement Learning pdf

Yinlam Chow, Mohammad Ghavamzadeh, Brandon Cui, 2020, ICLR.

Thompson Sampling with a Mixture Prior

B. Kveton, M. Zaheer, M. Ghavamzadeh, 2021, AISTATS.

Automatic Policy Synthesis to Improve the Safety of Nonlinear Dynamical Systems pdf

Bernhard Schölkopf, Arash Mehrjou, Mohammad Ghavamzadeh, 2020, ArXiv.

Constrained Stochastic Optimal Control with a Baseline Performance Guarantee

M. Ghavamzadeh, Yinlam Chow, 2014, 1410.2726.

Active Model Estimation in Markov Decision Processes

Alessandro Lazaric, Mohammad Ghavamzadeh, Matteo Pirotta, 2020, UAI.

Binary Classification with Bounded Abstention Rate pdf

Tara Javidi, Mohammad Ghavamzadeh, Shubhanshu Shekhar, 2019, ArXiv.

Improved Algorithms for Conservative Exploration in Bandits pdf

Alessandro Lazaric, Mohammad Ghavamzadeh, Matteo Pirotta, 2020, AAAI.

Speedy Q-Learning

H. Kappen, R. Munos, M. Ghavamzadeh, 2011, NIPS.

Bayesian Reinforcement Learning

Pascal Poupart, Shie Mannor, M. Ghavamzadeh, 2010, Encyclopedia of Machine Learning.

Fixed-Budget Best-Arm Identification in Structured Bandits

B. Kveton, M. Ghavamzadeh, Javad Azizi, 2021, IJCAI.

Active Learning for Classification With Abstention

Tara Javidi, Mohammad Ghavamzadeh, Shubhanshu Shekhar, 2021, IEEE Journal on Selected Areas in Information Theory.

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

M. Ghavamzadeh, P. Fieguth, Xiaochun Cao, 2020, Inf. Fusion.

Factual and Personalized Recommendations using Language Models and Reinforcement Learning

M. Ghavamzadeh, Yinlam Chow, Guy Tennenholtz, 2023, ArXiv.

DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models

P. Abbeel, M. Ghavamzadeh, Craig Boutilier, 2023, NeurIPS.

Preference Elicitation with Soft Attributes in Interactive Recommendation

M. Ghavamzadeh, Yinlam Chow, Erdem Biyik, 2023, arXiv.org.

Bayesian Reinforcement Learning: A Survey

Aviv Tamar, Shie Mannor, M. Ghavamzadeh, 2015, Found. Trends Mach. Learn..

Hierarchical Average Reward Reinforcement Learning

M. Ghavamzadeh, S. Mahadevan, 2022 .

Non-Stationary Latent Bandits pdf

Craig Boutilier, Amr Ahmed, Branislav Kveton, 2020, ArXiv.

Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management

M. Ghavamzadeh, Craig Boutilier, Yinlam Chow, 2023, NeurIPS.

Maximum Entropy Model Correction in Reinforcement Learning

M. Ghavamzadeh, Amir-massoud Farahmand, Mete Kemertas, 2023, ArXiv.

High-Confidence Off-Policy Evaluation

P. Thomas, M. Ghavamzadeh, Georgios Theocharous, 2015, AAAI.