Sayak Ray Chowdhury

According to our database1, Sayak Ray Chowdhury authored at least 25 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2024
Provably Robust DPO: Aligning Language Models with Noisy Feedback.
CoRR, 2024

Provably Sample Efficient RLHF via Active Preference Optimization.
CoRR, 2024

2023
GAR-meets-RAG Paradigm for Zero-Shot Information Retrieval.
CoRR, 2023

Differentially Private Reward Estimation with Preference Feedback.
CoRR, 2023

On Differentially Private Federated Linear Contextual Bandits.
CoRR, 2023

Combinatorial categorized bandits with expert rankings.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards.
Proceedings of the International Conference on Machine Learning, 2023

Distributed Differential Privacy in Multi-Armed Bandits.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Bregman Deviations of Generic Exponential Families.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Exploration in Linear Bandits with Rich Action Sets and its Implications for Inference.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Model Selection in Reinforcement Learning with General Function Approximations.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Shuffle Private Linear Contextual Bandits.
Proceedings of the International Conference on Machine Learning, 2022

Value Function Approximations via Kernel Embeddings for No-Regret Reinforcement Learning.
Proceedings of the Asian Conference on Machine Learning, 2022

Differentially Private Regret Minimization in Episodic Markov Decision Processes.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Model Selection with Near Optimal Rates for Reinforcement Learning with General Model Classes.
CoRR, 2021

Adaptive Control of Differentially Private Linear Quadratic Systems.
Proceedings of the IEEE International Symposium on Information Theory, 2021

Reinforcement Learning in Parametric MDPs with Exponential Families.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

No-regret Algorithms for Multi-task Bayesian Optimization.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
No-Regret Reinforcement Learning with Value Function Approximation: a Kernel Embedding Approach.
CoRR, 2020

Active Learning of Conditional Mean Embeddings via Bayesian Optimisation.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

2019
On Batch Bayesian Optimization.
CoRR, 2019

Bayesian Optimization under Heavy-tailed Payoffs.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Online Learning in Kernelized Markov Decision Processes.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2017
On Kernelized Multi-armed Bandits.
Proceedings of the 34th International Conference on Machine Learning, 2017

Misspecified Linear Bandits.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017


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