Han, Andi

29 publications

NeurIPS 2025 ACT as Human: Multimodal Large Language Model Data Annotation with Critical Thinking Lequan Lin, Dai Shi, Andi Han, Feng Chen, Qiuzheng Chen, Jiawen Li, Zhaoyang Li, Jiyuan Zhang, Zhenbang Sun, Junbin Gao

ICML 2025 Can Diffusion Models Learn Hidden Inter-Feature Rules Behind Images? Yujin Han, Andi Han, Wei Huang, Chaochao Lu, Difan Zou

ICLRW 2025 Can Diffusion Models Learn Hidden Inter-Feature Rules Behind Images? Yujin Han, Andi Han, Wei Huang, Chaochao Lu, Difan Zou

ICLR 2025 Diffusing to the Top: Boost Graph Neural Networks with Minimal Hyperparameter Tuning Lequan Lin, Dai Shi, Andi Han, Zhiyong Wang, Junbin Gao

ICML 2025 Efficient Optimization with Orthogonality Constraint: A Randomized Riemannian Submanifold Method Andi Han, Pierre-Louis Poirion, Akiko Takeda

NeurIPS 2025 Generalization Bound of Gradient Flow Through Training Trajectory and Data-Dependent Kernel Yilan Chen, Zhichao Wang, Wei Huang, Andi Han, Taiji Suzuki, Arya Mazumdar

NeurIPS 2025 How Does Label Noise Gradient Descent Improve Generalization in the Low SNR Regime? Wei Huang, Andi Han, Yujin Song, Yilan Chen, Denny Wu, Difan Zou, Taiji Suzuki

ICLR 2025 On the Feature Learning in Diffusion Models Andi Han, Wei Huang, Yuan Cao, Difan Zou

ICLR 2025 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

ICML 2025 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

ICML 2025 Provable In-Context Vector Arithmetic via Retrieving Task Concepts Dake Bu, Wei Huang, Andi Han, Atsushi Nitanda, Qingfu Zhang, Hau-San Wong, Taiji Suzuki

ICLRW 2025 SpecSTG: A Fast Spectral Diffusion Framework for Probabilistic Spatio-Temporal Traffic Forecasting Lequan Lin, Dai Shi, Andi Han, Junbin Gao

ICLR 2025 When Graph Neural Networks Meet Dynamic Mode Decomposition Dai Shi, Lequan Lin, Andi Han, Zhiyong Wang, Yi Guo, Junbin Gao

NeurIPS 2024 A Framework for Bilevel Optimization on Riemannian Manifolds Andi Han, Bamdev Mishra, Pratik Jawanpuria, Akiko Takeda

MLJ 2024 Differentially Private Riemannian Optimization Andi Han, Bamdev Mishra, Pratik Jawanpuria, Junbin Gao

TMLR 2024 From Continuous Dynamics to Graph Neural Networks: Neural Diffusion and Beyond Andi Han, Dai Shi, Lequan Lin, Junbin Gao

NeurIPS 2024 On the Comparison Between Multi-Modal and Single-Modal Contrastive Learning Wei Huang, Andi Han, Yongqiang Chen, Yuan Cao, Zhiqiang Xu, Taiji Suzuki

NeurIPS 2024 Provably Transformers Harness Multi-Concept Word Semantics for Efficient In-Context Learning Dake Bu, Wei Huang, Andi Han, Atsushi Nitanda, Taiji Suzuki, Qingfu Zhang, Hau-San Wong

MLJ 2024 Riemannian Block SPD Coupling Manifold and Its Application to Optimal Transport Andi Han, Bamdev Mishra, Pratik Jawanpuria, Junbin Gao

ICML 2024 Riemannian Coordinate Descent Algorithms on Matrix Manifolds Andi Han, Pratik Jawanpuria, Bamdev Mishra

NeurIPS 2024 SLTrain: A Sparse Plus Low Rank Approach for Parameter and Memory Efficient Pretraining Andi Han, Jiaxiang Li, Wei Huang, Mingyi Hong, Akiko Takeda, Pratik Jawanpuria, Bamdev Mishra

ICMLW 2024 Secondary Structure-Guided Novel Protein Sequence Generation with Latent Graph Diffusion Yutong Hu, Yang Tan, Andi Han, Lirong Zheng, Liang Hong, Bingxin Zhou

ACML 2023 A New Perspective on the Expressive Equivalence Between Graph Convolution and Attention Models Dai Shi, Zhiqi Shao, Andi Han, Yi Guo, Gao Junbin

TMLR 2023 Improved Differentially Private Riemannian Optimization: Fast Sampling and Variance Reduction Saiteja Utpala, Andi Han, Pratik Jawanpuria, Bamdev Mishra

TMLR 2023 Nonconvex-Nonconcave Min-Max Optimization on Riemannian Manifolds Andi Han, Bamdev Mishra, Pratik Jawanpuria, Junbin Gao

AISTATS 2023 Riemannian Accelerated Gradient Methods via Extrapolation Andi Han, Bamdev Mishra, Pratik Jawanpuria, Junbin Gao

NeurIPSW 2022 Rieoptax: Riemannian Optimization in JAX Saiteja Utpala, Andi Han, Pratik Jawanpuria, Bamdev Mishra

NeurIPS 2021 On Riemannian Optimization over Positive Definite Matrices with the Bures-Wasserstein Geometry Andi Han, Bamdev Mishra, Pratik Kumar Jawanpuria, Junbin Gao

IJCAI 2021 Riemannian Stochastic Recursive Momentum Method for Non-Convex Optimization Andi Han, Junbin Gao