Thanh Nguyen-Tang

According to our database, Thanh Nguyen-Tang authored at least 18 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Offline Multitask Representation Learning for Reinforcement Learning.

Haque Ishfaq, Thanh Nguyen-Tang, Songtao Feng, Raman Arora, Mengdi Wang, Ming Yin, Doina Precup

CoRR, 2024

2023

A Cosine Similarity-based Method for Out-of-Distribution Detection.

Hieu Ngoc Nguyen, Nguyen Hung-Quang, The-Anh Ta, Thanh Nguyen-Tang, Khoa D. Doan, Hoang Thanh-Tung

CoRR, 2023

Provably Efficient Neural Offline Reinforcement Learning via Perturbed Rewards.

Thanh Nguyen-Tang, Raman Arora

CoRR, 2023

Optimistic Rates for Multi-Task Representation Learning.

Austin Watkins, Enayat Ullah, Thanh Nguyen-Tang, Raman Arora

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling and Beyond.

Thanh Nguyen-Tang, Raman Arora

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Multi-Agent Learning with Heterogeneous Linear Contextual Bandits.

Anh Do, Thanh Nguyen-Tang, Raman Arora

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

VIPeR: Provably Efficient Algorithm for Offline RL with Neural Function Approximation.

Thanh Nguyen-Tang, Raman Arora

Proceedings of the Eleventh International Conference on Learning Representations, 2023

SigFormer: Signature Transformers for Deep Hedging.

Anh Tong, Thanh Nguyen-Tang, Dongeun Lee, Toan M. Tran, Jaesik Choi

Proceedings of the 4th ACM International Conference on AI in Finance, 2023

TIPI: Test Time Adaptation with Transformation Invariance.

A. Tuan Nguyen, Thanh Nguyen-Tang, Ser-Nam Lim, Philip H. S. Torr

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation.

Thanh Nguyen-Tang, Ming Yin, Sunil Gupta, Svetha Venkatesh, Raman Arora

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

On Sample Complexity of Offline Reinforcement Learning with Deep ReLU Networks in Besov Spaces.

Thanh Nguyen-Tang, Sunil Gupta, Hung Tran-The, Svetha Venkatesh

Trans. Mach. Learn. Res., 2022

Two-Stage Neural Contextual Bandits for Personalised News Recommendation.

Mengyan Zhang, Thanh Nguyen-Tang, Fangzhao Wu, Zhenyu He, Xing Xie, Cheng Soon Ong

CoRR, 2022

On Practical Reinforcement Learning: Provable Robustness, Scalability, and Statistical Efficiency.

Thanh Nguyen-Tang

CoRR, 2022

Learning Fractional White Noises in Neural Stochastic Differential Equations.

Anh Tong, Thanh Nguyen-Tang, Toan M. Tran, Jaesik Choi

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization.

Thanh Nguyen-Tang, Sunil Gupta, A. Tuan Nguyen, Svetha Venkatesh

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Combining Online Learning and Offline Learning for Contextual Bandits with Deficient Support.

Hung Tran-The, Sunil Gupta, Thanh Nguyen-Tang, Santu Rana, Svetha Venkatesh

CoRR, 2021

On Finite-Sample Analysis of Offline Reinforcement Learning with Deep ReLU Networks.

Thanh Nguyen-Tang, Sunil Gupta, Hung Tran-The, Svetha Venkatesh

CoRR, 2021

Distributional Reinforcement Learning via Moment Matching.

Thanh Nguyen-Tang, Sunil Gupta, Svetha Venkatesh

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021