Shalabh Bhatnagar

14 papers · 2006–2025 · 8 venues · across top CS/AI venues

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Achievements

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+8 more ↓

🗺️ Taxonomy Completionist (28) 🏃 Academic Marathon · Full 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Gold 🐣 Hot Topic Early Bird

🏆 Keyword Champion 🌟 Keyword Trendsetter Combo (3) 🔬 Deep Specialist (10) 🧭 Keyword Pioneer 📈 Trend Setter 🌈 Renaissance Researcher (5) 💎 Century Club · Bronze 🗃️ Keyword Collector (72)

Venues

NeurIPS (5) AAAI (3) AISTATS (1) CoRL (1) ICCV (1) ICML (1) JMLR (1) UAI (1)

Top co-authors

Richard S. Sutton (4) Csaba Szepesvári (3) Prashansa Panda (2) Hengshuai Yao (2) Shishir Kolathaya (2) Lokesh Krishna (1) Ashish K Jayant (1) Prashanth L.A. (1) Joseph Modayil (1) Doina Precup (1)

Research topics

Machine Learning (11) Reinforcement Learning (11) Methods (11) Artificial Intelligence (7) Core AI (7) Optimization & Theory (7) Learning Types · Machine Learning (6) Deep Learning (3) Applications · Reinforcement Learning (2) Core Methods (2) Learning Types · Deep Learning (2) Data Science & Analytics (1) Knowledge & Reasoning (1) Mathematics & Optimization (1) Applications · Data Science & Analytics (1)

Keywords

reinforcement learning (5) value function (4) temporal difference learning (4) function approximation (4) sample complexity (3) average reward (3) stochastic approximation (3) convergence analysis (3) policy gradient (2) stochastic gradient descent (2) policy evaluation (2) constrained markov decision process (2) model-based reinforcement learning (2) markov decision process (2) temporal abstraction (2) hierarchical reinforcement learning (1) visual reinforcement learning (1) policy learning (1) policy iteration (1) autonomous driving (1)

Papers

One Encoder to Rule them All: Representation Learning for Model-free Visual Reinforcement Learning using Fourier Neural Operators ICCV 2025 Two-Timescale Critic-Actor for Average Reward MDPs with Function Approximation AAAI 2025 A Cubic-regularized Policy Newton Algorithm for Reinforcement Learning AISTATS 2024 Finite-Time Analysis of Three-Timescale Constrained Actor-Critic and Constrained Natural Actor-Critic Algorithms. UAI 2024 Off-Policy Average Reward Actor-Critic with Deterministic Policy Search ICML 2023 Gradient Temporal Difference with Momentum: Stability and Convergence AAAI 2022 Model-based Safe Deep Reinforcement Learning via a Constrained Proximal Policy Optimization Algorithm NeurIPS 2022 Hierarchical Average Reward Policy Gradient Algorithms (Student Abstract) AAAI 2020 Robust Quadrupedal Locomotion on Sloped Terrains: A Linear Policy Approach CoRL 2020 Universal Option Models NeurIPS 2014 Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation NeurIPS 2009 Multi-Step Dyna Planning for Policy Evaluation and Control NeurIPS 2009 Incremental Natural Actor-Critic Algorithms NeurIPS 2007 A Simulation-Based Algorithm for Ergodic Control of Markov Chains Conditioned on Rare Events JMLR 2006