Thanh Nguyen-Tang
20 papers · 2021–2025 · 9 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
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Research topics
Machine Learning
(15)
Learning Types
(10)
Artificial Intelligence
(9)
Optimization & Theory
(9)
Reinforcement Learning
(8)
Methods
(8)
Core AI
(6)
Deep Learning
(5)
Mathematics & Optimization
(5)
Application Areas
(5)
Learning Paradigms
(4)
Core Methods
(3)
Optimization
(3)
Healthcare & Medicine
(2)
Natural Language Processing
(2)
Keywords
offline reinforcement learning
(4)
transfer learning
(4)
representation learning
(3)
neural network
(3)
data coverage
(2)
regret bound
(2)
domain generalization
(2)
medical domain
(2)
policy regret
(2)
multi-task learning
(2)
contextual bandit
(2)
distribution shift
(2)
function approximation
(2)
markov game
(2)
multi-task representation learning
(2)
multi-agent learning
(2)
uncertainty quantification
(1)
image generation
(1)
markov decision processes
(1)
entropy minimization
(1)
Papers
Fair Domain Generalization with Heterogeneous Sensitive Attributes Across Domains
WACV 2025
MultiMed: Multilingual Medical Speech Recognition via Attention Encoder Decoder
ACL 2025
MultiMed-ST: Large-scale Many-to-many Multilingual Medical Speech Translation
EMNLP 2025
Neural ODE Transformers: Analyzing Internal Dynamics and Adaptive Fine-tuning
ICLR 2025
Policy-Regret Minimization in Markov Games with Function Approximation
ICML 2025
Wicked Oddities: Selectively Poisoning for Effective Clean-Label Backdoor Attacks
ICLR 2025
Adversarially Robust Multi-task Representation Learning
NeurIPS 2024
Learning in Markov Games with Adaptive Adversaries: Policy Regret, Fundamental Barriers, and Efficient Algorithms
NeurIPS 2024
Offline Multitask Representation Learning for Reinforcement Learning
NeurIPS 2024
On The Statistical Complexity of Offline Decision-Making
ICML 2024
Domain Generalization with Interpolation Robustness
ACML 2023
Multi-Agent Learning with Heterogeneous Linear Contextual Bandits
NeurIPS 2023
On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation
AAAI 2023
On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling and Beyond
NeurIPS 2023
Optimistic Rates for Multi-Task Representation Learning
NeurIPS 2023
TIPI: Test Time Adaptation With Transformation Invariance
CVPR 2023
VIPeR: Provably Efficient Algorithm for Offline RL with Neural Function Approximation
ICLR 2023
Learning Fractional White Noises in Neural Stochastic Differential Equations
NeurIPS 2022
Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization
ICLR 2022
Distributional Reinforcement Learning via Moment Matching
AAAI 2021