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ORCIDSayak Ray Chowdhury
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Conference and Workshop Papers
- 2024
[c21]Sayak Ray Chowdhury, Xingyu Zhou, Nagarajan Natarajan:
Differentially Private Reward Estimation with Preference Feedback. AISTATS 2024: 4843-4851- [c20]Xingyu Zhou, Sayak Ray Chowdhury:
On Differentially Private Federated Linear Contextual Bandits. ICLR 2024 - [c19]Sayak Ray Chowdhury, Anush Kini, Nagarajan Natarajan:
Provably Robust DPO: Aligning Language Models with Noisy Feedback. ICML 2024 - [c18]Shikhar Mohan, Deepak Saini, Anshul Mittal, Sayak Ray Chowdhury, Bhawna Paliwal, Jian Jiao, Manish Gupta, Manik Varma:
OAK: Enriching Document Representations using Auxiliary Knowledge for Extreme Classification. ICML 2024 - 2023
- [c17]Debangshu Banerjee, Avishek Ghosh, Sayak Ray Chowdhury, Aditya Gopalan:
Exploration in Linear Bandits with Rich Action Sets and its Implications for Inference. AISTATS 2023: 8233-8262 - [c16]Sayak Ray Chowdhury, Patrick Saux, Odalric Maillard, Aditya Gopalan:
Bregman Deviations of Generic Exponential Families. COLT 2023: 394-449 - [c15]Sayak Ray Chowdhury, Xingyu Zhou:
Distributed Differential Privacy in Multi-Armed Bandits. ICLR 2023 - [c14]Yulian Wu, Xingyu Zhou, Sayak Ray Chowdhury, Di Wang:
Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards. ICML 2023: 37880-37918 - [c13]Sayak Ray Chowdhury, Gaurav Sinha, Nagarajan Natarajan, Amit Sharma:
Combinatorial categorized bandits with expert rankings. UAI 2023: 403-412 - 2022
- [c12]Sayak Ray Chowdhury, Xingyu Zhou:
Differentially Private Regret Minimization in Episodic Markov Decision Processes. AAAI 2022: 6375-6383 - [c11]Sayak Ray Chowdhury, Rafael Oliveira:
Value Function Approximations via Kernel Embeddings for No-Regret Reinforcement Learning. ACML 2022: 249-264 - [c10]Sayak Ray Chowdhury, Xingyu Zhou:
Shuffle Private Linear Contextual Bandits. ICML 2022: 3984-4009 - [c9]Avishek Ghosh, Sayak Ray Chowdhury
:
Model Selection in Reinforcement Learning with General Function Approximations. ECML/PKDD (4) 2022: 148-164 - 2021
- [c8]Sayak Ray Chowdhury, Aditya Gopalan, Odalric-Ambrym Maillard:
Reinforcement Learning in Parametric MDPs with Exponential Families. AISTATS 2021: 1855-1863 - [c7]Sayak Ray Chowdhury, Aditya Gopalan:
No-regret Algorithms for Multi-task Bayesian Optimization. AISTATS 2021: 1873-1881 - [c6]Sayak Ray Chowdhury, Xingyu Zhou, Ness B. Shroff:
Adaptive Control of Differentially Private Linear Quadratic Systems. ISIT 2021: 485-490 - 2020
- [c5]Sayak Ray Chowdhury, Rafael Oliveira, Fabio Ramos:
Active Learning of Conditional Mean Embeddings via Bayesian Optimisation. UAI 2020: 1119-1128 - 2019
- [c4]Sayak Ray Chowdhury, Aditya Gopalan:
Online Learning in Kernelized Markov Decision Processes. AISTATS 2019: 3197-3205 - [c3]Sayak Ray Chowdhury, Aditya Gopalan:
Bayesian Optimization under Heavy-tailed Payoffs. NeurIPS 2019: 13790-13801 - 2017
- [c2]Avishek Ghosh, Sayak Ray Chowdhury, Aditya Gopalan:
Misspecified Linear Bandits. AAAI 2017: 3761-3767 - [c1]Sayak Ray Chowdhury, Aditya Gopalan:
On Kernelized Multi-armed Bandits. ICML 2017: 844-853
Informal and Other Publications
- 2024
- [i24]Nirjhar Das, Souradip Chakraborty, Aldo Pacchiano, Sayak Ray Chowdhury:
Provably Sample Efficient RLHF via Active Preference Optimization. CoRR abs/2402.10500 (2024) - [i23]Sayak Ray Chowdhury, Anush Kini, Nagarajan Natarajan:
Provably Robust DPO: Aligning Language Models with Noisy Feedback. CoRR abs/2403.00409 (2024) - [i22]Seongho Son, William Bankes, Sayak Ray Chowdhury, Brooks Paige, Ilija Bogunovic:
Right Now, Wrong Then: Non-Stationary Direct Preference Optimization under Preference Drift. CoRR abs/2407.18676 (2024) - [i21]Sankha Das, Sayak Ray Chowdhury, Nishanth Chandran, Divya Gupta, Satya Lokam, Rahul Sharma:
Communication Efficient Secure and Private Multi-Party Deep Learning. IACR Cryptol. ePrint Arch. 2024: 1471 (2024) - 2023
- [i20]Xingyu Zhou, Sayak Ray Chowdhury:
On Differentially Private Federated Linear Contextual Bandits. CoRR abs/2302.13945 (2023) - [i19]Yulian Wu, Xingyu Zhou, Sayak Ray Chowdhury, Di Wang:
Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards. CoRR abs/2306.01121 (2023) - [i18]Sayak Ray Chowdhury, Xingyu Zhou, Nagarajan Natarajan:
Differentially Private Reward Estimation with Preference Feedback. CoRR abs/2310.19733 (2023) - [i17]Daman Arora, Anush Kini, Sayak Ray Chowdhury, Nagarajan Natarajan, Gaurav Sinha, Amit Sharma:
GAR-meets-RAG Paradigm for Zero-Shot Information Retrieval. CoRR abs/2310.20158 (2023) - 2022
- [i16]Sayak Ray Chowdhury, Patrick Saux, Odalric-Ambrym Maillard, Aditya Gopalan:
Bregman Deviations of Generic Exponential Families. CoRR abs/2201.07306 (2022) - [i15]Sayak Ray Chowdhury, Xingyu Zhou:
Shuffle Private Linear Contextual Bandits. CoRR abs/2202.05567 (2022) - [i14]Sayak Ray Chowdhury, Xingyu Zhou:
Distributed Differential Privacy in Multi-Armed Bandits. CoRR abs/2206.05772 (2022) - [i13]Avishek Ghosh, Sayak Ray Chowdhury:
Model Selection in Reinforcement Learning with General Function Approximations. CoRR abs/2207.02992 (2022) - [i12]Debangshu Banerjee, Avishek Ghosh, Sayak Ray Chowdhury, Aditya Gopalan:
Exploration in Linear Bandits with Rich Action Sets and its Implications for Inference. CoRR abs/2207.11597 (2022) - 2021
- [i11]Avishek Ghosh, Sayak Ray Chowdhury, Kannan Ramchandran:
Model Selection with Near Optimal Rates for Reinforcement Learning with General Model Classes. CoRR abs/2107.05849 (2021) - [i10]Sayak Ray Chowdhury, Xingyu Zhou, Ness B. Shroff:
Adaptive Control of Differentially Private Linear Quadratic Systems. CoRR abs/2108.11563 (2021) - [i9]Sayak Ray Chowdhury, Xingyu Zhou:
Differentially Private Regret Minimization in Episodic Markov Decision Processes. CoRR abs/2112.10599 (2021) - 2020
- [i8]Sayak Ray Chowdhury, Aditya Gopalan:
No-regret Algorithms for Multi-task Bayesian Optimization. CoRR abs/2008.08885 (2020) - [i7]Sayak Ray Chowdhury, Rafael Oliveira:
No-Regret Reinforcement Learning with Value Function Approximation: a Kernel Embedding Approach. CoRR abs/2011.07881 (2020) - 2019
- [i6]Sayak Ray Chowdhury, Aditya Gopalan:
Bayesian Optimization under Heavy-tailed Payoffs. CoRR abs/1909.07040 (2019) - [i5]Sayak Ray Chowdhury, Aditya Gopalan:
On Batch Bayesian Optimization. CoRR abs/1911.01032 (2019) - [i4]Sayak Ray Chowdhury, Aditya Gopalan:
On Online Learning in Kernelized Markov Decision Processes. CoRR abs/1911.01871 (2019) - 2018
- [i3]Sayak Ray Chowdhury, Aditya Gopalan:
Online Learning in Kernelized Markov Decision Processes. CoRR abs/1805.08052 (2018) - 2017
- [i2]Sayak Ray Chowdhury, Aditya Gopalan:
On Kernelized Multi-armed Bandits. CoRR abs/1704.00445 (2017) - [i1]Avishek Ghosh, Sayak Ray Chowdhury, Aditya Gopalan:
Misspecified Linear Bandits. CoRR abs/1704.06880 (2017)
Coauthor Index
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