Mohammad Gheshlaghi azar

21 papers · 2011–2025 · 6 venues · across top CS/AI venues

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Achievements

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🗺️ Taxonomy Completionist (38) 🏃 Academic Marathon · Half 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird

🧭 Keyword Pioneer 🤝 Dynamic Duo (14) 🚀 Conference Pioneer 🔥 Unstoppable · Bronze 💎 Century Club · Bronze 🗃️ Keyword Collector (99)

Venues

ICML (7) NeurIPS (5) ICLR (4) AISTATS (2) JMLR (2) EMNLP (1)

Top co-authors

Rémi Munos (14) Bilal Piot (9) Michal Valko (8) Yunhao Tang (5) Mark Rowland (5) Olivier Pietquin (4) Will Dabney (4) Zhaohan Daniel Guo (4) Matthieu Geist (4) Daniele Calandriello (4)

Research topics

Machine Learning (18) Reinforcement Learning (14) Learning Types · Machine Learning (14) Methods (13) Artificial Intelligence (9) Optimization & Theory (9) Deep Learning (8) Core AI (6) Learning Types · Deep Learning (6) Applications (3) Core Methods (3) Learning Paradigms (3) Mathematics & Optimization (2) Models (2) Optimization (2)

Keywords

reinforcement learning (7) self-supervised learning (5) mirror descent (3) representation learning (3) policy gradient (3) regret bound (2) policy optimization (2) latent representation (2) off-policy learning (2) contrastive learning (2) policy iteration (2) transfer learning (2) nash equilibrium (2) distributional reinforcement learning (2) preference optimization (2) markov decision process (2) temporal difference learning (2) dynamic programming (2) human feedback (2) large language model (2)

Papers

Self-Improving Robust Preference Optimization ICLR 2025 A General Theoretical Paradigm to Understand Learning from Human Preferences AISTATS 2024 An Analysis of Quantile Temporal-Difference Learning JMLR 2024 Contrastive Policy Gradient: Aligning LLMs on sequence-level scores in a supervised-friendly fashion EMNLP 2024 Nash Learning from Human Feedback ICML 2024 Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice ICML 2023 Understanding Self-Predictive Learning for Reinforcement Learning ICML 2023 BYOL-Explore: Exploration by Bootstrapped Prediction NeurIPS 2022 Large-Scale Representation Learning on Graphs via Bootstrapping ICLR 2022 Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity NeurIPS 2021 Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning ICML 2020 Bootstrap Your Own Latent - A New Approach to Self-Supervised Learning NeurIPS 2020 Fast computation of Nash Equilibria in Imperfect Information Games ICML 2020 Hindsight Credit Assignment NeurIPS 2019 Noisy Networks For Exploration ICLR 2018 The Reactor: A fast and sample-efficient Actor-Critic agent for Reinforcement Learning ICLR 2018 Minimax Regret Bounds for Reinforcement Learning ICML 2017 Online Stochastic Optimization under Correlated Bandit Feedback ICML 2014 Sequential Transfer in Multi-armed Bandit with Finite Set of Models NeurIPS 2013 Dynamic Policy Programming JMLR 2012 Dynamic Policy Programming with Function Approximation AISTATS 2011