Offline Policy Evaluation and Optimization under Confounding. - Kevin Tan; Yangyi Lu; Chinmaya Kausik; Yixin Wang; Ambuj Tewari (CoRR, 2022)

Learning Mixtures of Markov Chains and MDPs. - Chinmaya Kausik; Kevin Tan; Ambuj Tewari (ICML, 2023)

Generalization Error without Independence: Denoising, Linear Regression, and Transfer Learning. - Chinmaya Kausik; Kashvi Srivastava; Rishi Sonthalia (CoRR, 2023)

Offline Policy Evaluation and Optimization Under Confounding. - Chinmaya Kausik; Yangyi Lu; Kevin Tan; Maggie Makar; Yixin Wang; Ambuj Tewari (AISTATS, 2024)

A Framework for Partially Observed Reward-States in RLHF. - Chinmaya Kausik; Mirco Mutti; Aldo Pacchiano; Ambuj Tewari (CoRR, 2024)

Leveraging Offline Data in Linear Latent Bandits. - Chinmaya Kausik; Kevin Tan; Ambuj Tewari (CoRR, 2024)

Double Descent and Overfitting under Noisy Inputs and Distribution Shift for Linear Denoisers. - Chinmaya Kausik; Kashvi Srivastava; Rishi Sonthalia (Trans. Mach. Learn. Res., 2024)

A Theoretical Framework for Partially-Observed Reward States in RLHF. - Chinmaya Kausik; Mirco Mutti; Aldo Pacchiano; Ambuj Tewari (ICLR, 2025)