| 2026 | AAAI | On the Learning Dynamics of Two-layer Linear Networks with Label Noise SGD. | Tongcheng Zhang, Zhanpeng Zhou, Mingze Wang, Andi Han, Wei Huang, Taiji Suzuki, Junchi Yan |
| 2025 | COLT | The Adaptive Complexity of Finding a Stationary Point. | Huanjian Zhou, Andi Han, Akiko Takeda, Masashi Sugiyama |
| 2025 | ICLR | On the Feature Learning in Diffusion Models. | Andi Han, Wei Huang, Yuan Cao, Difan Zou |
| 2025 | ICLR | On the Optimization and Generalization of Two-layer Transformers with Sign Gradient Descent. | Bingrui Li, Wei Huang, Andi Han, Zhanpeng Zhou, Taiji Suzuki, Jun Zhu, Jianfei Chen |
| 2025 | ICLR | Diffusing to the Top: Boost Graph Neural Networks with Minimal Hyperparameter Tuning. | Lequan Lin, Dai Shi, Andi Han, Zhiyong Wang, Junbin Gao |
| 2025 | ICLR | When Graph Neural Networks Meet Dynamic Mode Decomposition. | Dai Shi, Lequan Lin, Andi Han, Zhiyong Wang, Yi Guo, Junbin Gao |
| 2025 | ICML | Provable In-Context Vector Arithmetic via Retrieving Task Concepts. | Dake Bu, Wei Huang, Andi Han, Atsushi Nitanda, Qingfu Zhang, Hau-San Wong, Taiji Suzuki |
| 2025 | ICML | On the Role of Label Noise in the Feature Learning Process. | Andi Han, Wei Huang, Zhanpeng Zhou, Gang Niu, Wuyang Chen, Junchi Yan, Akiko Takeda, Taiji Suzuki |
| 2025 | ICML | Can Diffusion Models Learn Hidden Inter-Feature Rules Behind Images? | Yujin Han, Andi Han, Wei Huang, Chaochao Lu, Difan Zou |
| 2025 | ICML | Efficient Optimization with Orthogonality Constraint: a Randomized Riemannian Submanifold Method. | Andi Han, Pierre-Louis Poirion, Akiko Takeda |
| 2025 | IJCNN | SpecSTG: A Fast Spectral Diffusion Framework for Probabilistic Spatio-Temporal Traffic Forecasting. | Lequan Lin, Dai Shi, Andi Han, Junbin Gao |
| 2024 | ICML | Riemannian coordinate descent algorithms on matrix manifolds. | Andi Han, Pratik Jawanpuria, Bamdev Mishra |
| 2023 | ACML | A New Perspective On the Expressive Equivalence Between Graph Convolution and Attention Models. | Dai Shi, Zhiqi Shao, Andi Han, Yi Guo, Junbin Gao |
| 2023 | AISTATS | Riemannian Accelerated Gradient Methods via Extrapolation. | Andi Han, Bamdev Mishra, Pratik Jawanpuria, Junbin Gao |
| 2023 | IJCNN | Fixed Point Laplacian Mapping: A Geometrically Correct Manifold Learning Algorithm. | Dai Shi, Andi Han, Yi Guo, Junbin Gao |
| 2021 | IJCAI | Riemannian Stochastic Recursive Momentum Method for non-Convex Optimization. | Andi Han, Junbin Gao |