Jianhao Ma

Jianhao Ma Ph.D. candidate at Department of Industrial and Operational Engineering University of Michigan, Ann Arbor, United States Email: jianhao [at] umich [dot] edu [Google Scholar][Curriculum Vitae] [GitHub]

About me

I'm currently a fifth-year Ph.D. student at Umich. I am fortunate to be advised by Professor Salar Fattahi. My research focus on developing efficient and robust machine learning models. I welcome future collaborations. Please feel free to contact me via Email!

I am on the 2024-2025 academic job market.

Research Interests

• General optimization and generalization in modern machine learning.

• Robust machine learning.

• Quantization.

Preprints

• Can Learning Be Explained By Local Optimality In Low-rank Matrix Recovery? [arxiv]
  Major revision at Mathematics of Operations Research
  INFORMS Junior Faculty Interest Group (JFIG) Paper Competition – Second Place
  Jianhao Ma, Salar Fattahi
  

Publications

• Convergence of Gradient Descent with Small Initialization for Unregularized Matrix Completion [paper][arxiv]
  Conference on Learning Theory (COLT) 2024
  Jianhao Ma, Salar Fattahi
  

• Robust Sparse Mean Estimation via Incremental Learning [arxiv]
  ICLR Workshop on Bridging the Gap Between Practice and Theory in Deep Learning 2024
  Jianhao Ma, Rui Ray Chen, Yinghui He, Salar Fattahi, Wei Hu
  

• 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)
  Katta Murty Prize for Best Research Paper on Optimization
  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

• October 2024: I will attend INFORMS Annual Meeting.

• March 2024: I will attend INFORMS Optimization Society Conference.

• March 2024: Our paper has been accepted at ICLR BGPT workshop.

• March 2024: Thrilled to receive Rackham Predoctoral Fellowship.

• February 2024: I will intern at FAIR in Meta with Dr. Lin Xiao this summer.

• February 2024: New paper about the global convergence of GD for unregularized matrix completion.

Services

Reviewer of IEEE TIT, IEEE TSP, ICML, NeurIPS, ICLR, AISTATS.

Quote

Always consider a problem under the minimum structure in which it makes sense. —— Gustave Choquet