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Mohammad Ghavamzadeh

Mohammad Ghavamzadeh

D-Index & Metrics

Computer Science

D-Index
57
Citations
10541
World Ranking
3897
National Ranking
1845

Overview

Mohammad Ghavamzadeh is a researcher affiliated with Amazon in the United States. Their academic work primarily spans the field of Computer Science, with a focus on Artificial Intelligence, Management Science and Operations Research, and subareas such as Computer Networks and Communications, Computational Theory and Mathematics, and Computer Vision and Pattern Recognition.

Their research topics cover a range of subjects, including:

  • Advanced Bandit Algorithms Research
  • Reinforcement Learning in Robotics
  • Machine Learning and Algorithms
  • Topic Modeling
  • Machine Learning and Data Classification
  • Data Stream Mining Techniques
  • Optimization and Search Problems

Ghavamzadeh has an extensive publication record, with many papers appearing in prominent venues. Their frequent publication outlets include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Information Fusion
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • IEEE Journal on Selected Areas in Information Theory

Notable recent papers authored by Ghavamzadeh include:

  • A review of uncertainty quantification in deep learning: Techniques, applications and challenges (2021, Information Fusion)
  • Finite-Sample Analysis of Proximal Gradient TD Algorithms (2020, arXiv (Cornell University))
  • Aligning Text-to-Image Models using Human Feedback (2023, arXiv (Cornell University))
  • Mirror Descent Policy Optimization (2020, arXiv (Cornell University))
  • DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models (2023, arXiv (Cornell University))

Throughout their career, Ghavamzadeh has collaborated frequently with several researchers, forming recurring co-authorship links. These include:

  • Branislav Kveton (9 collaborations)
  • Yinlam Chow (9 collaborations)
  • Craig Boutilier (9 collaborations)
  • Marek Petrik (7 collaborations)
  • Alessandro Lazaric (5 collaborations)

Best Publications

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

    Moloud Abdar;Farhad Pourpanah;Sadiq Hussain;Dana Rezazadegan

  • Natural actor-critic algorithms

    Shalabh Bhatnagar;Richard S. Sutton;Mohammad Ghavamzadeh;Mark Lee

  • Bayesian Reinforcement Learning: A Survey

    Mohammad Ghavamzadeh;Shie Mannor;Joelle Pineau;Aviv Tamar

  • Best Arm Identification: A Unified Approach to Fixed Budget and Fixed Confidence

    Victor Gabillon;Mohammad Ghavamzadeh;Alessandro Lazaric

  • A Lyapunov-based Approach to Safe Reinforcement Learning

    Yinlam Chow;Ofir Nachum;Edgar A. Duéñez-Guzmán;Mohammad Ghavamzadeh

  • Risk-Constrained Reinforcement Learning with Percentile Risk Criteria

    Yinlam Chow;Mohammad Ghavamzadeh;Lucas Janson;Marco Pavone

  • High confidence off-policy evaluation

    Philip S. Thomas;Georgios Theocharous;Mohammad Ghavamzadeh

  • Incremental Natural Actor-Critic Algorithms

    Shalabh Bhatnagar;Mohammad Ghavamzadeh;Mark Lee;Richard S Sutton

  • Benchmarking Batch Deep Reinforcement Learning Algorithms.

    Scott Fujimoto;Edoardo Conti;Mohammad Ghavamzadeh;Joelle Pineau

  • Hierarchical multi-agent reinforcement learning

    Rajbala Makar;Sridhar Mahadevan;Mohammad Ghavamzadeh

  • Lyapunov-based Safe Policy Optimization for Continuous Control

    Yinlam Chow;Ofir Nachum;Aleksandra Faust;Edgar Duenez-Guzman

  • Hierarchical multi-agent reinforcement learning

    Mohammad Ghavamzadeh;Sridhar Mahadevan;Rajbala Makar

  • High Confidence Policy Improvement

    Philip Thomas;Georgios Theocharous;Mohammad Ghavamzadeh

  • Regularized Policy Iteration

    Amir M. Farahmand;Mohammad Ghavamzadeh;Shie Mannor;Csaba Szepesvári

  • More Robust Doubly Robust Off-policy Evaluation

    Mehrdad Farajtabar;Yinlam Chow;Mohammad Ghavamzadeh

  • Algorithms for CVaR Optimization in MDPs

    Yinlam Chow;Mohammad Ghavamzadeh

  • Personalized ad recommendation systems for life-time value optimization with guarantees

    Georgios Theocharous;Philip S. Thomas;Mohammad Ghavamzadeh

  • Ad Recommendation Systems for Life-Time Value Optimization

    Georgios Theocharous;Philip S. Thomas;Mohammad Ghavamzadeh

  • Bayesian Multi-Task Reinforcement Learning

    Alessandro Lazaric;Mohammad Ghavamzadeh

  • Finite-sample analysis of proximal gradient TD algorithms

    Bo Liu;Ji Liu;Mohammad Ghavamzadeh;Sridhar Mahadevan

  • Speedy Q-Learning

    Mohammad Ghavamzadeh;Hilbert J. Kappen;Mohammad G. Azar;Rémi Munos

  • Approximate modified policy iteration and its application to the game of Tetris

    Bruno Scherrer;Mohammad Ghavamzadeh;Victor Gabillon;Boris Lesner

  • Convex Optimization: Algorithms and Complexity

    Mohammed Ghavamzadeh;Shie Mannor;Joelle Pineau;Aviv Tamar

Frequent Co-Authors

Alessandro Lazaric
Alessandro Lazaric Facebook (United States)
Sridhar Mahadevan
Sridhar Mahadevan University of Massachusetts Amherst
Shie Mannor
Shie Mannor Technion – Israel Institute of Technology
Branislav Kveton
Branislav Kveton Adobe Systems (United States)
Csaba Szepesvári
Csaba Szepesvári University of Alberta
Rémi Munos
Rémi Munos French Institute for Research in Computer Science and Automation - INRIA
Craig Boutilier
Craig Boutilier Google (United States)
Aviv Tamar
Aviv Tamar Technion – Israel Institute of Technology
Ji Liu
Ji Liu Facebook (United States)
Tara Javidi
Tara Javidi University of California, San Diego

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