Wei Hu - RankMe

36 papers A* 13A 2Journal 18Unranked 2

Year	Rank	Type	Title / Venue / Authors
2024	A*	`conf`	Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce Grokking. ICLR Kaifeng Lyu, Jikai Jin, Zhiyuan Li, Simon Shaolei Du, Jason D. Lee, Wei Hu
2023	J	`jnl`	Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce Grokking. CoRR Kaifeng Lyu, Jikai Jin, Zhiyuan Li, Simon S. Du, Jason D. Lee, Wei Hu
2021	A*	`conf`	Few-Shot Learning via Learning the Representation, Provably. ICLR Simon Shaolei Du, Wei Hu, Sham M. Kakade, Jason D. Lee, Qi Lei
2021	A*	`conf`	Impact of Representation Learning in Linear Bandits. ICLR Jiaqi Yang, Wei Hu, Jason D. Lee, Simon Shaolei Du
2021	A*	`conf`	Near-Optimal Linear Regression under Distribution Shift. ICML Qi Lei, Wei Hu, Jason D. Lee
2021	J	`jnl`	Near-Optimal Linear Regression under Distribution Shift. CoRR Qi Lei, Wei Hu, Jason D. Lee
2021	—	`—`	Understanding Deep Learning via Analyzing Dynamics of Gradient Descent Wei Hu
2021	A	`conf`	When is particle filtering efficient for planning in partially observed linear dynamical systems? UAI Simon S. Du, Wei Hu, Zhiyuan Li, Ruoqi Shen, Zhao Song, Jiajun Wu
2020	J	`jnl`	Few-Shot Learning via Learning the Representation, Provably. CoRR Simon S. Du, Wei Hu, Sham M. Kakade, Jason D. Lee, Qi Lei
2020	J	`jnl`	Provable Benefits of Representation Learning in Linear Bandits. CoRR Jiaqi Yang, Wei Hu, Jason D. Lee, Simon S. Du
2020	A*	`conf`	Simple and Effective Regularization Methods for Training on Noisily Labeled Data with Generalization Guarantee. ICLR Wei Hu, Zhiyuan Li, Dingli Yu
2020	J	`jnl`	When is Particle Filtering Efficient for POMDP Sequential Planning? CoRR Simon S. Du, Wei Hu, Zhiyuan Li, Ruoqi Shen, Zhao Song, Jiajun Wu
2019	—	`conf`	A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks. ICLR (Poster) Sanjeev Arora, Nadav Cohen, Noah Golowich, Wei Hu
2019	J	`jnl`	Enhanced Convolutional Neural Tangent Kernels. CoRR Zhiyuan Li, Ruosong Wang, Dingli Yu, Simon S. Du, Wei Hu, Ruslan Salakhutdinov, Sanjeev Arora
2019	A*	`conf`	Explaining Landscape Connectivity of Low-cost Solutions for Multilayer Nets. NeurIPS Rohith Kuditipudi, Xiang Wang, Holden Lee, Yi Zhang, Zhiyuan Li, Wei Hu, Rong Ge, Sanjeev Arora
2019	J	`jnl`	Explaining Landscape Connectivity of Low-cost Solutions for Multilayer Nets. CoRR Rohith Kuditipudi, Xiang Wang, Holden Lee, Yi Zhang, Zhiyuan Li, Wei Hu, Sanjeev Arora, Rong Ge
2019	A*	`conf`	Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks. ICML Sanjeev Arora, Simon S. Du, Wei Hu, Zhiyuan Li, Ruosong Wang
2019	J	`jnl`	Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks. CoRR Sanjeev Arora, Simon S. Du, Wei Hu, Zhiyuan Li, Ruosong Wang
2019	A*	`conf`	Implicit Regularization in Deep Matrix Factorization. NeurIPS Sanjeev Arora, Nadav Cohen, Wei Hu, Yuping Luo
2019	J	`jnl`	Implicit Regularization in Deep Matrix Factorization. CoRR Sanjeev Arora, Nadav Cohen, Wei Hu, Yuping Luo
2019	A	`conf`	Linear Convergence of the Primal-Dual Gradient Method for Convex-Concave Saddle Point Problems without Strong Convexity. AISTATS Simon S. Du, Wei Hu
2019	A*	`conf`	On Exact Computation with an Infinitely Wide Neural Net. NeurIPS Sanjeev Arora, Simon S. Du, Wei Hu, Zhiyuan Li, Ruslan Salakhutdinov, Ruosong Wang
2019	J	`jnl`	On Exact Computation with an Infinitely Wide Neural Net. CoRR Sanjeev Arora, Simon S. Du, Wei Hu, Zhiyuan Li, Ruslan Salakhutdinov, Ruosong Wang
2019	J	`jnl`	Understanding Generalization of Deep Neural Networks Trained with Noisy Labels. CoRR Wei Hu, Zhiyuan Li, Dingli Yu
2019	A*	`conf`	Width Provably Matters in Optimization for Deep Linear Neural Networks. ICML Simon S. Du, Wei Hu
2019	J	`jnl`	Width Provably Matters in Optimization for Deep Linear Neural Networks. CoRR Simon S. Du, Wei Hu
2018	J	`jnl`	A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks. CoRR Sanjeev Arora, Nadav Cohen, Noah Golowich, Wei Hu
2018	A*	`conf`	Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced. NeurIPS Simon S. Du, Wei Hu, Jason D. Lee
2018	J	`jnl`	Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced. CoRR Simon S. Du, Wei Hu, Jason D. Lee
2018	A*	`conf`	An Analysis of the t-SNE Algorithm for Data Visualization. COLT Sanjeev Arora, Wei Hu, Pravesh K. Kothari
2018	J	`jnl`	An Analysis of the t-SNE Algorithm for Data Visualization. CoRR Sanjeev Arora, Wei Hu, Pravesh K. Kothari
2018	J	`jnl`	Linear Convergence of the Primal-Dual Gradient Method for Convex-Concave Saddle Point Problems without Strong Convexity. CoRR Simon S. Du, Wei Hu
2018	A*	`conf`	Online Improper Learning with an Approximation Oracle. NeurIPS Elad Hazan, Wei Hu, Yuanzhi Li, Zhiyuan Li
2018	J	`jnl`	Online Improper Learning with an Approximation Oracle. CoRR Elad Hazan, Wei Hu, Yuanzhi Li, Zhiyuan Li
2017	—	`conf`	Linear Convergence of a Frank-Wolfe Type Algorithm over Trace-Norm Balls. NIPS Zeyuan Allen-Zhu, Elad Hazan, Wei Hu, Yuanzhi Li
2017	J	`jnl`	Linear Convergence of a Frank-Wolfe Type Algorithm over Trace-Norm Balls. CoRR Zeyuan Allen-Zhu, Elad Hazan, Wei Hu, Yuanzhi Li