Shalabh Bhatnagar

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

Achievements

+7 more ↓

🌍 Conference Polyglot (8) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🏃 Academic Marathon (19)

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (8) 🏆 Keyword Champion (3) 📈 Trend Setter 🗃️ Keyword Collector (65) 💎 Century Club (14)

Conferences

NIPS (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)

Keywords

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

Papers

Two-Timescale Critic-Actor for Average Reward MDPs with Function Approximation AAAI 2025 One Encoder to Rule them All: Representation Learning for Model-free Visual Reinforcement Learning using Fourier Neural Operators ICCV 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 NIPS 2022 Robust Quadrupedal Locomotion on Sloped Terrains: A Linear Policy Approach CORL 2020 Hierarchical Average Reward Policy Gradient Algorithms (Student Abstract) AAAI 2020 Universal Option Models NIPS 2014 Multi-Step Dyna Planning for Policy Evaluation and Control NIPS 2009 Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation NIPS 2009 Incremental Natural Actor-Critic Algorithms NIPS 2007 A Simulation-Based Algorithm for Ergodic Control of Markov Chains Conditioned on Rare Events JMLR 2006