Kalathil, Dileep

20 publications

L4DC 2025 Bridging Distributionally Robust Learning and Offline RL: An Approach to Mitigate Distribution Shift and Partial Data Coverage Kishan Panaganti, Zaiyan Xu, Dileep Kalathil, Mohammad Ghavamzadeh

NeurIPS 2025 Robust LLM Alignment via Distributionally Robust Direct Preference Optimization Zaiyan Xu, Sushil Vemuri, Kishan Panaganti, Dileep Kalathil, Rahul Jain, Deepak Ramachandran

AISTATS 2025 Transformers Are Provably Optimal In-Context Estimators for Wireless Communications Vishnu Teja Kunde, Vicram Rajagopalan, Chandra Shekhara Kaushik Valmeekam, Krishna Narayanan, Jean-Francois Chamberland, Dileep Kalathil, Srinivas Shakkottai

ICMLW 2024 Bridging Distributionally Robust Learning and Offline RL: An Approach to Mitigate Distribution Shift and Partial Data Coverage Kishan Panaganti, Zaiyan Xu, Dileep Kalathil, Mohammad Ghavamzadeh

NeurIPS 2024 Federated Ensemble-Directed Offline Reinforcement Learning Desik Rengarajan, Nitin Ragothaman, Dileep Kalathil, Srinivas Shakkottai

AAAI 2024 Meta-Learning-Based Adaptive Stability Certificates for Dynamical Systems Amit Jena, Dileep Kalathil, Le Xie

NeurIPS 2024 Risk-Averse Fine-Tuning of Large Language Models Sapana Chaudhary, Ujwal Dinesha, Dileep Kalathil, Srinivas Shakkottai

TMLR 2023 Dynamic Regret Analysis of Safe Distributed Online Optimization for Convex and Non-Convex Problems Ting-Jui Chang, Sapana Chaudhary, Dileep Kalathil, Shahin Shahrampour

ICMLW 2023 Federated Ensemble-Directed Offline Reinforcement Learning Desik Rengarajan, Nitin Ragothaman, Dileep Kalathil, Srinivas Shakkottai

AISTATS 2023 Improved Sample Complexity Bounds for Distributionally Robust Reinforcement Learning Zaiyan Xu, Kishan Panaganti, Dileep Kalathil

NeurIPS 2023 Natural Actor-Critic for Robust Reinforcement Learning with Function Approximation Ruida Zhou, Tao Liu, Min Cheng, Dileep Kalathil, P. R. Kumar, Chao Tian

AISTATS 2022 Sample Complexity of Robust Reinforcement Learning with a Generative Model Kishan Panaganti, Dileep Kalathil

NeurIPS 2022 Anchor-Changing Regularized Natural Policy Gradient for Multi-Objective Reinforcement Learning Ruida Zhou, Tao Liu, Dileep Kalathil, P. R. Kumar, Chao Tian

NeurIPS 2022 DOPE: Doubly Optimistic and Pessimistic Exploration for Safe Reinforcement Learning Archana Bura, Aria HasanzadeZonuzy, Dileep Kalathil, Srinivas Shakkottai, Jean-Francois Chamberland

NeurIPS 2022 Enhanced Meta Reinforcement Learning via Demonstrations in Sparse Reward Environments Desik Rengarajan, Sapana Chaudhary, Jaewon Kim, Dileep Kalathil, Srinivas Shakkottai

ICLR 2022 Reinforcement Learning with Sparse Rewards Using Guidance from Offline Demonstration Desik Rengarajan, Gargi Vaidya, Akshay Sarvesh, Dileep Kalathil, Srinivas Shakkottai

NeurIPS 2022 Robust Reinforcement Learning Using Offline Data Kishan Panaganti, Zaiyan Xu, Dileep Kalathil, Mohammad Ghavamzadeh

AISTATS 2021 Reinforcement Learning for Mean Field Games with Strategic Complementarities Kiyeob Lee, Desik Rengarajan, Dileep Kalathil, Srinivas Shakkottai

NeurIPS 2021 Learning Policies with Zero or Bounded Constraint Violation for Constrained MDPs Tao Liu, Ruida Zhou, Dileep Kalathil, Panganamala Kumar, Chao Tian

ICML 2021 Robust Reinforcement Learning Using Least Squares Policy Iteration with Provable Performance Guarantees Kishan Panaganti Badrinath, Dileep Kalathil