Linear Convergence of a Frank-Wolfe Type Algorithm over Trace-Norm Balls. - Zeyuan Allen-Zhu; Elad Hazan; Wei Hu 014; Yuanzhi Li (NIPS, 2017)

An Analysis of the t-SNE Algorithm for Data Visualization. - Sanjeev Arora; Wei Hu 014; Pravesh K. Kothari (COLT, 2018)

Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced. - Simon S. Du; Wei Hu 014; Jason D. Lee (NeurIPS, 2018)

Online Improper Learning with an Approximation Oracle. - Elad Hazan; Wei Hu 014; Yuanzhi Li; Zhiyuan Li 005 (NeurIPS, 2018)

Linear Convergence of the Primal-Dual Gradient Method for Convex-Concave Saddle Point Problems without Strong Convexity. - Simon S. Du; Wei Hu 014 (AISTATS, 2019)

A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks. - Sanjeev Arora; Nadav Cohen; Noah Golowich; Wei Hu 014 (ICLR (Poster), 2019)

Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks. - Sanjeev Arora; Simon S. Du; Wei Hu 014; Zhiyuan Li 005; Ruosong Wang (ICML, 2019)

Width Provably Matters in Optimization for Deep Linear Neural Networks. - Simon S. Du; Wei Hu 014 (ICML, 2019)

Implicit Regularization in Deep Matrix Factorization. - Sanjeev Arora; Nadav Cohen; Wei Hu 014; Yuping Luo (NeurIPS, 2019)

On Exact Computation with an Infinitely Wide Neural Net. - Sanjeev Arora; Simon S. Du; Wei Hu 014; Zhiyuan Li 005; Ruslan Salakhutdinov; Ruosong Wang (NeurIPS, 2019)

Explaining Landscape Connectivity of Low-cost Solutions for Multilayer Nets. - Rohith Kuditipudi; Xiang Wang 011; Holden Lee; Yi Zhang 074; Zhiyuan Li 005; Wei Hu 014; Rong Ge 001; Sanjeev Arora (NeurIPS, 2019)

Understanding Generalization of Deep Neural Networks Trained with Noisy Labels. - Wei Hu 014; Zhiyuan Li 005; Dingli Yu (CoRR, 2019)

Enhanced Convolutional Neural Tangent Kernels. - Zhiyuan Li 005; Ruosong Wang; Dingli Yu; Simon S. Du; Wei Hu 014; Ruslan Salakhutdinov; Sanjeev Arora (CoRR, 2019)

Simple and Effective Regularization Methods for Training on Noisily Labeled Data with Generalization Guarantee. - Wei Hu 014; Zhiyuan Li 005; Dingli Yu (ICLR, 2020)

When is Particle Filtering Efficient for POMDP Sequential Planning? - Simon S. Du; Wei Hu 014; Zhiyuan Li 005; Ruoqi Shen; Zhao Song 002; Jiajun Wu 001 (CoRR, 2020)

Provable Benefits of Representation Learning in Linear Bandits. - Jiaqi Yang 001; Wei Hu 014; Jason D. Lee; Simon S. Du (CoRR, 2020)

Few-Shot Learning via Learning the Representation, Provably. - Simon Shaolei Du; Wei Hu 014; Sham M. Kakade; Jason D. Lee; Qi Lei (ICLR, 2021)

Impact of Representation Learning in Linear Bandits. - Jiaqi Yang 001; Wei Hu 014; Jason D. Lee; Simon Shaolei Du (ICLR, 2021)

Near-Optimal Linear Regression under Distribution Shift. - Qi Lei; Wei Hu 014; Jason D. Lee (ICML, 2021)

When is particle filtering efficient for planning in partially observed linear dynamical systems? - Simon S. Du; Wei Hu 014; Zhiyuan Li 005; Ruoqi Shen; Zhao Song 002; Jiajun Wu 001 (UAI, 2021)

Understanding Deep Learning via Analyzing Dynamics of Gradient Descent - Wei Hu 014 (2021)

Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce Grokking. - Kaifeng Lyu; Jikai Jin; Zhiyuan Li 005; Simon Shaolei Du; Jason D. Lee; Wei Hu 014 (ICLR, 2024)