| 2026 | AAAI | DP-NCB: Privacy Preserving Fair Bandits. | Dhruv Sarkar, Nishant Pandey, Sayak Ray Chowdhury |
| 2025 | ICML | Right Now, Wrong Then: Non-Stationary Direct Preference Optimization under Preference Drift. | Seongho Son, William Bankes, Sayak Ray Chowdhury, Brooks Paige, Ilija Bogunovic |
| 2024 | AISTATS | Differentially Private Reward Estimation with Preference Feedback. | Sayak Ray Chowdhury, Xingyu Zhou, Nagarajan Natarajan |
| 2024 | ICLR | On Differentially Private Federated Linear Contextual Bandits. | Xingyu Zhou, Sayak Ray Chowdhury |
| 2024 | ICML | Provably Robust DPO: Aligning Language Models with Noisy Feedback. | Sayak Ray Chowdhury, Anush Kini, Nagarajan Natarajan |
| 2024 | ICML | OAK: Enriching Document Representations using Auxiliary Knowledge for Extreme Classification. | Shikhar Mohan, Deepak Saini, Anshul Mittal, Sayak Ray Chowdhury, Bhawna Paliwal, Jian Jiao, Manish Gupta, Manik Varma |
| 2023 | AISTATS | Exploration in Linear Bandits with Rich Action Sets and its Implications for Inference. | Debangshu Banerjee, Avishek Ghosh, Sayak Ray Chowdhury, Aditya Gopalan |
| 2023 | COLT | Bregman Deviations of Generic Exponential Families. | Sayak Ray Chowdhury, Patrick Saux, Odalric Maillard, Aditya Gopalan |
| 2023 | ICLR | Distributed Differential Privacy in Multi-Armed Bandits. | Sayak Ray Chowdhury, Xingyu Zhou |
| 2023 | ICML | Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards. | Yulian Wu, Xingyu Zhou, Sayak Ray Chowdhury, Di Wang |
| 2023 | UAI | Combinatorial categorized bandits with expert rankings. | Sayak Ray Chowdhury, Gaurav Sinha, Nagarajan Natarajan, Amit Sharma |
| 2022 | AAAI | Differentially Private Regret Minimization in Episodic Markov Decision Processes. | Sayak Ray Chowdhury, Xingyu Zhou |
| 2022 | ACML | Value Function Approximations via Kernel Embeddings for No-Regret Reinforcement Learning. | Sayak Ray Chowdhury, Rafael Oliveira |
| 2022 | ICML | Shuffle Private Linear Contextual Bandits. | Sayak Ray Chowdhury, Xingyu Zhou |
| 2021 | AISTATS | No-regret Algorithms for Multi-task Bayesian Optimization. | Sayak Ray Chowdhury, Aditya Gopalan |
| 2021 | AISTATS | Reinforcement Learning in Parametric MDPs with Exponential Families. | Sayak Ray Chowdhury, Aditya Gopalan, Odalric-Ambrym Maillard |
| 2021 | ISIT | Adaptive Control of Differentially Private Linear Quadratic Systems. | Sayak Ray Chowdhury, Xingyu Zhou, Ness B. Shroff |
| 2020 | UAI | Active Learning of Conditional Mean Embeddings via Bayesian Optimisation. | Sayak Ray Chowdhury, Rafael Oliveira, Fabio Ramos |
| 2019 | AISTATS | Online Learning in Kernelized Markov Decision Processes. | Sayak Ray Chowdhury, Aditya Gopalan |
| 2017 | AAAI | Misspecified Linear Bandits. | Avishek Ghosh, Sayak Ray Chowdhury, Aditya Gopalan |
| 2017 | ICML | On Kernelized Multi-armed Bandits. | Sayak Ray Chowdhury, Aditya Gopalan |