Publications
Publications
( * indicates equal contribution. )
Predicting Properties of Quantum Systems with Conditional Generative Models [Code]
Haoxiang Wang, Maurice Weber, Josh Izaac, Cedric Yen-Yu Lin
arXiv, 2022
Invariant Feature Subspace Recovery for Multi-Class Classification
Gargi Balasubramaniam, Haoxiang Wang, Han Zhao
NeurIPS Distribution Shifts (DistShift) Workshop, 2022
Generative Gradual Domain Adaptation with Optimal Transport
Yifei He*, Haoxiang Wang*, Han Zhao
ICML Principles of Distribution Shift (PODS) Workshop, 2022.
Understanding Gradual Domain Adaptation: Improved Analysis, Optimal Path and Beyond [Code]
Haoxiang Wang, Bo Li, Han Zhao
International Conference on Machine Learning (ICML), 2022
Provable Domain Generalization via Invariant-Feature Subspace Recovery [Code]
Haoxiang Wang, Haozhe Si, Bo Li, Han Zhao
International Conference on Machine Learning (ICML), 2022
Mao Ye, Ruichen Jiang, Haoxiang Wang, Dhruv Choudhary, Xiaocong Du, Bhargav Bhushanam, Aryan Mokhtari, Arun Kejariwal, Qiang Liu
Uncertainty in Artificial Intelligence (UAI), 2022
Global Convergence of MAML and Theory-Inspired Neural Architecture Search for Few-Shot Learning [Code]
Haoxiang Wang*, Yite Wang*, Ruoyu Sun, Bo Li
Conference on Computer Vision and Pattern Recognition (CVPR), 2022
Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation [Code, Video, Slides]
Haoxiang Wang, Han Zhao, Bo Li
International Conference on Machine Learning (ICML), 2021
Global Convergence and Generalization Bound of Gradient-Based Meta-Learning with Deep Neural Nets
Haoxiang Wang, Ruoyu Sun, Bo Li
arXiv, 2020
Learning Positive Functions with Pseudo Mirror Descent
Yingxiang Yang, Haoxiang Wang, Negar Kiyavash, Niao He.
Advances in Neural Information Processing Systems (NeurIPS), 2019 (spotlight, acceptance rate: 164/6743 = 2.4%)