Model-Free Robust Reinforcement Learning with Linear Function Approximation. - Kishan Panaganti; Dileep M. Kalathil (CoRR, 2020)

Sample Complexity of Model-Based Robust Reinforcement Learning. - Kishan Panaganti; Dileep Kalathil (CDC, 2021)

Off-Policy Evaluation Using Information Borrowing and Context-Based Switching. - Sutanoy Dasgupta; Yabo Niu; Kishan Panaganti; Dileep Kalathil; Debdeep Pati; Bani K. Mallick (CoRR, 2021)

Bounded Regret for Finitely Parameterized Multi-Armed Bandits. - Kishan Panaganti; Dileep M. Kalathil (IEEE Control. Syst. Lett., 2021)

Sample Complexity of Robust Reinforcement Learning with a Generative Model. - Kishan Panaganti; Dileep M. Kalathil (AISTATS, 2022)

Robust Reinforcement Learning using Offline Data. - Kishan Panaganti; Zaiyan Xu; Dileep Kalathil; Mohammad Ghavamzadeh (NeurIPS, 2022)

Interaction-Grounded Learning for Recommender Systems. - Jessica Maghakian; Kishan Panaganti; Paul Mineiro; Akanksha Saran; Cheng Tan (ORSUM@RecSys, 2022)

Improved Sample Complexity Bounds for Distributionally Robust Reinforcement Learning. - Zaiyan Xu; Kishan Panaganti; Dileep Kalathil (AISTATS, 2023)

Distributionally Robust Behavioral Cloning for Robust Imitation Learning. - Kishan Panaganti; Zaiyan Xu; Dileep Kalathil; Mohammad Ghavamzadeh (CDC, 2023)

Personalized Reward Learning with Interaction-Grounded Learning (IGL). - Jessica Maghakian; Paul Mineiro; Kishan Panaganti; Mark Rucker; Akanksha Saran; Cheng Tan (ICLR, 2023)

Model-Free Robust ϕ-Divergence Reinforcement Learning Using Both Offline and Online Data. - Kishan Panaganti; Adam Wierman; Eric Mazumdar (ICML, 2024)

Distributionally Robust Constrained Reinforcement Learning under Strong Duality. - Zhengfei Zhang; Kishan Panaganti; Laixi Shi; Yanan Sui; Adam Wierman; Yisong Yue (RLJ, 2024)

Tractable Equilibrium Computation in Markov Games through Risk Aversion. - Eric Mazumdar; Kishan Panaganti; Laixi Shi (CoRR, 2024)

Hybrid Transfer Reinforcement Learning: Provable Sample Efficiency from Shifted-Dynamics Data. - Chengrui Qu; Laixi Shi; Kishan Panaganti; Pengcheng You; Adam Wierman (AISTATS, 2025)

Tractable Multi-Agent Reinforcement Learning through Behavioral Economics. - Eric Mazumdar; Kishan Panaganti; Laixi Shi (ICLR, 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 (L4DC, 2025)

Distributionally Robust Direct Preference Optimization. - Zaiyan Xu; Sushil Vemuri; Kishan Panaganti; Dileep Kalathil; Rahul Jain 002; Deepak Ramachandran (CoRR, 2025)

KL-regularization Itself is Differentially Private in Bandits and RLHF. - Yizhou Zhang; Kishan Panaganti; Laixi Shi; Juba Ziani; Adam Wierman (CoRR, 2025)

Efficient Policy Optimization in Robust Constrained MDPs with Iteration Complexity Guarantees. - Sourav Ganguly; Arnob Ghosh; Kishan Panaganti; Adam Wierman (CoRR, 2025)

TARDIS STRIDE: A Spatio-Temporal Road Image Dataset and World Model for Autonomy. - Héctor Carrión; Yutong Bai; Víctor A. Hernández Castro; Kishan Panaganti; Ayush Zenith; Matthew Trang; Tony Zhang; Pietro Perona; Jitendra Malik (CoRR, 2025)

Risk-Averse Total-Reward Reinforcement Learning. - Xihong Su; Jia Lin Hau; Gersi Doko; Kishan Panaganti; Marek Petrik (CoRR, 2025)

Evolving Language Models without Labels: Majority Drives Selection, Novelty Promotes Variation. - Yujun Zhou 010; Zhenwen Liang; Haolin Liu; Wenhao Yu 002; Kishan Panaganti; Linfeng Song; Dian Yu 001; Xiangliang Zhang 001; Haitao Mi; Dong Yu 001 (CoRR, 2025)