Thanh Nguyen-Tang

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 25

Top Topics

Function Approximation

News Recommendation

Reinforcement Learning

Top Venues

Publications

Quang H. Nguyen, Nguyen Ngoc-Hieu, The-Anh Ta, Thanh Nguyen-Tang, Kok-Seng Wong, Hoang Thanh-Tung, Khoa D. Doan
Wicked Oddities: Selectively Poisoning for Effective Clean-Label Backdoor Attacks. CoRR (2024)
Thanh Nguyen-Tang, Raman Arora
On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling, and Beyond. CoRR (2024)
Haque Ishfaq, Thanh Nguyen-Tang, Songtao Feng, Raman Arora, Mengdi Wang, Ming Yin, Doina Precup
Offline Multitask Representation Learning for Reinforcement Learning. CoRR (2024)
Anh Do, Thanh Nguyen-Tang, Raman Arora
Multi-Agent Learning with Heterogeneous Linear Contextual Bandits. NeurIPS (2023)
Anh Tong, Thanh Nguyen-Tang, Dongeun Lee, Toan M. Tran, Jaesik Choi
SigFormer: Signature Transformers for Deep Hedging. ICAIF (2023)
Hieu Ngoc Nguyen, Nguyen Hung-Quang, The-Anh Ta, Thanh Nguyen-Tang, Khoa D. Doan, Hoang Thanh-Tung
A Cosine Similarity-based Method for Out-of-Distribution Detection. CoRR (2023)
Thanh Nguyen-Tang, Raman Arora
VIPeR: Provably Efficient Algorithm for Offline RL with Neural Function Approximation. ICLR (2023)
Anh Tong, Thanh Nguyen-Tang, Dongeun Lee, Toan M. Tran, Jaesik Choi
SigFormer: Signature Transformers for Deep Hedging. CoRR (2023)
Thanh Nguyen-Tang, Raman Arora
On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling and Beyond. NeurIPS (2023)
A. Tuan Nguyen, Thanh Nguyen-Tang, Ser-Nam Lim, Philip H. S. Torr
TIPI: Test Time Adaptation with Transformation Invariance. CVPR (2023)
Thong Bach, Anh Tong, Truong Son Hy, Vu Nguyen, Thanh Nguyen-Tang
Global Contrastive Learning for Long-Tailed Classification. Trans. Mach. Learn. Res. 2023 (2023)
Thanh Nguyen-Tang, Raman Arora
Provably Efficient Neural Offline Reinforcement Learning via Perturbed Rewards. CoRR (2023)
Thanh Nguyen-Tang, Ming Yin, Sunil Gupta, Svetha Venkatesh, Raman Arora
On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation. AAAI (2023)
Austin Watkins, Enayat Ullah, Thanh Nguyen-Tang, Raman Arora
Optimistic Rates for Multi-Task Representation Learning. NeurIPS (2023)
Ragja Palakkadavath, Thanh Nguyen-Tang, Hung Le, Svetha Venkatesh, Sunil Gupta
Domain Generalization with Interpolation Robustness. ACML (2023)
Thanh Nguyen-Tang, Sunil Gupta, A. Tuan Nguyen, Svetha Venkatesh
Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization. ICLR (2022)
Mengyan Zhang, Thanh Nguyen-Tang, Fangzhao Wu, Zhenyu He, Xing Xie, Cheng Soon Ong
Two-Stage Neural Contextual Bandits for Personalised News Recommendation. CoRR (2022)
Thanh Nguyen-Tang, Ming Yin, Sunil Gupta, Svetha Venkatesh, Raman Arora
On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation. CoRR (2022)
Thanh Nguyen-Tang, Sunil Gupta, Hung Tran-The, Svetha Venkatesh
On Sample Complexity of Offline Reinforcement Learning with Deep ReLU Networks in Besov Spaces. Trans. Mach. Learn. Res. 2022 (2022)
Anh Tong, Thanh Nguyen-Tang, Toan M. Tran, Jaesik Choi
Learning Fractional White Noises in Neural Stochastic Differential Equations. NeurIPS (2022)
Thanh Nguyen-Tang
On Practical Reinforcement Learning: Provable Robustness, Scalability, and Statistical Efficiency. CoRR (2022)
Thanh Nguyen-Tang, Sunil Gupta, Hung Tran-The, Svetha Venkatesh
On Finite-Sample Analysis of Offline Reinforcement Learning with Deep ReLU Networks. CoRR (2021)
Thanh Nguyen-Tang, Sunil Gupta, A. Tuan Nguyen, Svetha Venkatesh
Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization. CoRR (2021)
Hung Tran-The, Sunil Gupta, Thanh Nguyen-Tang, Santu Rana, Svetha Venkatesh
Combining Online Learning and Offline Learning for Contextual Bandits with Deficient Support. CoRR (2021)
Thanh Nguyen-Tang, Sunil Gupta, Svetha Venkatesh
Distributional Reinforcement Learning via Moment Matching. AAAI (2021)