About Me
I am a researcher at AI Theory Group of Huawei Noah’s Ark Lab. I obtained my Ph.D. degree in Probability and Mathematical Statistics from Academy of Mathematics and Systems Science, Chinese Academy of Sciences in 2022, under the supervision of Prof. Zhi-Ming Ma. Before that, I received my Bachelor’s Degree in Math from Central China Normal University in 2017.
Hiring: I am looking for research interns in Huawei Noah’s Ark Lab with strong machine learning and mathematical background. Please drop me an email if you are interested in machine learning theory, optimization, or generative model. Base: Beijing.
Research Interests
Optimization Theory
Statistical Learning
Deep Learning
Working Experience
2018.9-2020.3 Research Intern, Machine Learning Group of Microsoft Research Asia, supervisor Wei Chen
2020.4-2021.2 Research Intern, Speech & Language Processing Group of Huawei Noah’s Ark Lab, supervisor Lu Hou
2021.2-2022.5 Research Intern, AI Theory Group of Huawei Noah’s Ark Lab, supervisor Zhenguo Li
Publications
“*” means equally contribution, “†” means corresponding author
Continuous-time Riemannian SGD and SVRG Flows on Wasserstein Probabilistic Space
Mingyang Yi, Bohan Wang
Preprint
On the Generalization of Diffusion Model
Mingyang Yi, Jiacheng Sun, Zhenguo Li
Preprint
SA-Solver: Stochastic Adams Solver for Fast Sampling of Diffusion Models
Shuchen Xue, Mingyang Yi†, Weijian Luo, Shifeng Zhang, Jiacheng Sun, Zhenguo Li, Zhi-Ming Ma 37th Conference on Neural Information Processing Systems (NeurIPS 2023)
Breaking Correlation Shift via Conditional Invariant Regularizer
Mingyang Yi, Ruoyu Wang, Jiacheng Sun, Zhenguo Li, Zhi-Ming Ma
11th International Conference on Learning Representations (ICLR 2023)
Towards the Generalization of Contrastive Self-supervised Learning
Weiran Huang*, Mingyang Yi*, Xuyang Zhao*, Zihao Jiang
11th International Conference on Learning Representations (ICLR 2023)
Characterization of Excess Risk for Locally Strongly Convex Population Risk
Mingyang Yi*, Ruoyu Wang*, Zhi-Ming Ma
36th Conference on Neural Information Processing Systems (NeurIPS 2022)
Accelerating Training of Batch Normalization: A Manifold Perspective
Mingyang Yi
38th Uncertainty in Artificial Intelligence (UAI 2022).
Out-of-distribution Generalization with Causal Invariant Transformations
Ruoyu Wang*, Mingyang Yi*, Zhitang Chen, Shengyu Zhu
40th Computer Vision and Pattern Recognition (CVPR 2022)
Improved OOD Generalization via Adversarial Training and Pre-training
Mingyang Yi, Lu Hou, Jiacheng Sun, Lifeng Shang, Xin Jiang, Qun Liu, Zhi-Ming Ma
38th International Conference on Machine Learning (ICML 2021)
Reweighting Augmented Samples by Minimizing the Maximal Expected Loss
Mingyang Yi, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu, Zhi-Ming Ma
9th International Conference on Learning Representations (ICLR 2021)
BN-invariant Sharpness Regularizes the Training Model to Better Generalization
Mingyang Yi, Huishuai Zhang, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
29th International Joint Conference on Artificial Intelligence (IJCAI 2019)
Stablize Deep ResNets with A Sharp Scaling \tau
Huishuai Zhang, Da Yu, Mingyang Yi, Wei Chen, Tie-Yan Liu
Journal of Machine Learning
Improving Deep Learning by Regularized Scale-Free MSE of Representations
Xufang Luo, Mingyang Yi, Yunhong Wang
26th International Conference on Neural Information Processing (ICONIP 2019)
Awards
AMSS Presidential Scholarship, 2019
Excellent Intern at Huawei Noah’s Ark Lab, 2021
Chinese National Scholarship, 2021
ZhuLiYueHua Scholarship of the Chinese Academy of Sciences, 2022
Outstanding PhD Thesis of the Chinese Academy of Sciences, 2023
Academic Services
Conference Reviewer: ICML, ICLR, NeurIPS, AISTATS
Journal Reviewer: IJCV, TNNLS