Wei Hu

Wei Hu 

Wei Hu (胡威)
Ph.D. Student
Department of Computer Science
Princeton University

Email: huwei [at] cs [dot] princeton [dot] edu

[Google Scholar]


I am a third year PhD student in the Department of Computer Science at Princeton University, affiliated with the Theory Group, the Theoretical Machine Learning Group, and Sanjeev Arora’s Group. I am very fortunate to be advised by Sanjeev Arora. Previously, I did my undergrad at Tsinghua University, where I was a member of Yao Class.

I am interested in theory of machine learning and optimization.


(Authors are ordered alphabetically, unless otherwise noted)


Conference Publications


Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks

13th Annual Machine Learning Symposium at New York Academy of Sciences, March 2019, New York, NY, USA

On the Dynamics of Gradient Descent for Training Deep Neural Networks

Princeton-IAS Theoretical Machine Learning Seminar, October 2018, Princeton, NJ, USA

Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced

ICML 2018 Workshop on Modern Trends in Nonconvex Optimization for Machine Learning, July 2018, Stockholm, Sweden

An Analysis of the t-SNE Algorithm for Data Visualization

COLT, July 2018, Stockholm, Sweden

Linear Convergence of a Frank-Wolfe Type Algorithm over Trace-Norm Balls

NIPS, December 2017, Long Beach, CA, USA

New Characterizations in Turnstile Streams with Applications

CCC, May 2016, Tokyo, Japan

Combinatorial Multi-Armed Bandit with General Reward Functions

Microsoft Research Asia Theory Group Seminar, March 2016, Beijing, China


Princeton University


Selected Awards