Nguyen-Tang, Thanh

24 publications

WACV 2025 Fair Domain Generalization with Heterogeneous Sensitive Attributes Across Domains Ragja Palakkadavath, Hung Le, Thanh Nguyen-Tang, Sunil Gupta, Svetha Venkatesh

ICLR 2025 Neural ODE Transformers: Analyzing Internal Dynamics and Adaptive Fine-Tuning Anh Tong, Thanh Nguyen-Tang, Dongeun Lee, Duc Nguyen, Toan Tran, David Leo Wright Hall, Cheongwoong Kang, Jaesik Choi

NeurIPS 2025 Online Optimization for Offline Safe Reinforcement Learning Yassine Chemingui, Aryan Deshwal, Alan Fern, Thanh Nguyen-Tang, Jana Doppa

ICML 2025 Policy-Regret Minimization in Markov Games with Function Approximation Thanh Nguyen-Tang, Raman Arora

ICLR 2025 Wicked Oddities: Selectively Poisoning for Effective Clean-Label Backdoor Attacks Nguyen Hung-Quang, Ngoc-Hieu Nguyen, The-Anh Ta, Thanh Nguyen-Tang, Kok-Seng Wong, Hoang Thanh-Tung, Khoa D Doan

NeurIPS 2024 Adversarially Robust Multi-Task Representation Learning Austin Watkins, Thanh Nguyen-Tang, Enayat Ullah, Raman Arora

NeurIPS 2024 Learning in Markov Games with Adaptive Adversaries: Policy Regret, Fundamental Barriers, and Efficient Algorithms Thanh Nguyen-Tang, Raman Arora

NeurIPS 2024 Offline Multitask Representation Learning for Reinforcement Learning Haque Ishfaq, Thanh Nguyen-Tang, Songtao Feng, Raman Arora, Mengdi Wang, Ming Yin, Doina Precup

ICML 2024 On the Statistical Complexity of Offline Decision-Making Thanh Nguyen-Tang, Raman Arora

NeurIPSW 2023 Clean-Label Backdoor Attacks by Selectively Poisoning with Limited Information from Target Class Nguyen Hung-Quang, Ngoc-Hieu Nguyen, The-Anh Ta, Thanh Nguyen-Tang, Hoang Thanh-Tung, Khoa D Doan

ACML 2023 Domain Generalization with Interpolation Robustness Ragja Palakkadavath, Thanh Nguyen-Tang, Hung Le, Svetha Venkatesh, Sunil Gupta

TMLR 2023 Global Contrastive Learning for Long-Tailed Classification Thong Bach, Anh Tong, Truong Son Hy, Vu Nguyen, Thanh Nguyen-Tang

NeurIPS 2023 Multi-Agent Learning with Heterogeneous Linear Contextual Bandits Anh Do, Thanh Nguyen-Tang, Raman Arora

AAAI 2023 On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation Thanh Nguyen-Tang, Ming Yin, Sunil Gupta, Svetha Venkatesh, Raman Arora

NeurIPS 2023 On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling and Beyond Thanh Nguyen-Tang, Raman Arora

NeurIPS 2023 Optimistic Rates for Multi-Task Representation Learning Austin Watkins, Enayat Ullah, Thanh Nguyen-Tang, Raman Arora

CVPR 2023 TIPI: Test Time Adaptation with Transformation Invariance A. Tuan Nguyen, Thanh Nguyen-Tang, Ser-Nam Lim, Philip H.S. Torr

ICLR 2023 VIPeR: Provably Efficient Algorithm for Offline RL with Neural Function Approximation Thanh Nguyen-Tang, Raman Arora

NeurIPSW 2022 Improving Domain Generalization with Interpolation Robustness Ragja Palakkadavath, Thanh Nguyen-Tang, Sunil Gupta, Svetha Venkatesh

NeurIPSW 2022 Improving Domain Generalization with Interpolation Robustness Ragja Palakkadavath, Thanh Nguyen-Tang, Sunil Gupta, Svetha Venkatesh

NeurIPS 2022 Learning Fractional White Noises in Neural Stochastic Differential Equations Anh Tong, Thanh Nguyen-Tang, Toan Tran, Jaesik Choi

ICLR 2022 Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization Thanh Nguyen-Tang, Sunil Gupta, A. Tuan Nguyen, Svetha Venkatesh

TMLR 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

AAAI 2021 Distributional Reinforcement Learning via Moment Matching Thanh Nguyen-Tang, Sunil Gupta, Svetha Venkatesh