Thanh Nguyen-Tang

Orcid: 0000-0002-1917-2190

According to our database1, Thanh Nguyen-Tang authored at least 22 papers between 2021 and 2024.

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

Timeline

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Bibliography

2024
Wicked Oddities: Selectively Poisoning for Effective Clean-Label Backdoor Attacks.
CoRR, 2024

Offline Multitask Representation Learning for Reinforcement Learning.
CoRR, 2024

On The Statistical Complexity of Offline Decision-Making.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Global Contrastive Learning for Long-Tailed Classification.
Trans. Mach. Learn. Res., 2023

A Cosine Similarity-based Method for Out-of-Distribution Detection.
CoRR, 2023

Provably Efficient Neural Offline Reinforcement Learning via Perturbed Rewards.
CoRR, 2023

Optimistic Rates for Multi-Task Representation Learning.
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.
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.
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.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

SigFormer: Signature Transformers for Deep Hedging.
Proceedings of the 4th ACM International Conference on AI in Finance, 2023

TIPI: Test Time Adaptation with Transformation Invariance.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Domain Generalization with Interpolation Robustness.
Proceedings of the Asian Conference on Machine Learning, 2023

On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation.
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.
Trans. Mach. Learn. Res., 2022

Two-Stage Neural Contextual Bandits for Personalised News Recommendation.
CoRR, 2022

On Practical Reinforcement Learning: Provable Robustness, Scalability, and Statistical Efficiency.
CoRR, 2022

Learning Fractional White Noises in Neural Stochastic Differential Equations.
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.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Combining Online Learning and Offline Learning for Contextual Bandits with Deficient Support.
CoRR, 2021

On Finite-Sample Analysis of Offline Reinforcement Learning with Deep ReLU Networks.
CoRR, 2021

Distributional Reinforcement Learning via Moment Matching.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021


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