Jianhao Ma
About me
I'm currently a third-year Ph.D. candidate at Umich. I am fortunate to be advised by Professor Salar Fattahi. My research focus on understanding the pratical success of gradient-based algorithms based on trajectory analysis. I welcome future collaborations. Please feel free to contact me via Email!
Research Interests
General optimization and generalization in modern machine learning.
Algorithmic robust statistics.
Empirical process and its application.
Preprints
Robust Sparse Mean Estimation via Incremental Learning [arxiv]
Jianhao Ma, Rui Ray Chen, Yinghui He, Salar Fattahi, Wei Hu
On the Optimization Landscape of Burer-Monteiro Factorization: When do Global Solutions Correspond to Ground Truth? [arxiv]
Jianhao Ma, Salar Fattahi
Publications
Global Convergence of Sub-gradient Method for Robust Matrix Recovery: Small Initialization, Noisy Measurements, and Over-parameterization [paper]arxiv]
Journal of Machine Learning Research (JMLR) 2023
Jianhao Ma, Salar Fattahi
Behind the Scenes of Gradient Descent: A Trajectory Analysis via Basis Function Decomposition [paper][arxiv]
International Conference on Learning Representations (ICLR) 2023
Jianhao Ma, Lingjun Guo, Salar Fattahi
Blessing of Nonconvexity in Deep Linear Models: Depth Flattens the Optimization Landscape Around the True Solution [paper][arxiv]
Advances in Neural Information Processing Systems (NeurIPS) 2022 (Spotlight)
Jianhao Ma, Salar Fattahi
Towards Understanding Generalization via Decomposing Excess Risk Dynamics [paper] [arxiv]
International Conference on Learning Representations (ICLR) 2022
Jiaye Teng*, Jianhao Ma*, Yang Yuan
Sign-RIP: A Robust Restricted Isometry Property for Low-rank Matrix Recovery [paper][arxiv]
Jianhao Ma, Salar Fattahi
NeurIPS Workshop on Optimization for Machine Learning, 2021
News
Teaching
TA for IOE 473: Advanced Data Analytics, Winter 2023.
Conference Services
Reviewer of ICML, NeurIPS, ICLR, AISTATS.
Quate
Always consider a problem under the minimum structure in which it makes sense. —— Gustave Choquet
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