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]

About

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.

Publications

(Authors are ordered alphabetically, unless otherwise noted)

Talks

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

Teaching

Princeton University

Service

Selected Awards