384 citations · 1.3k across the 26 of their papers we have counts for
5 papers · 1 filter
A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks
Sanjeev Arora, Nadav Cohen, Noah Golowich +1
We analyze speed of convergence to global optimum for gradient descent training a deep linear neural network (parameterized as ) by minimizing t…
Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced
Simon S. Du, Wei Hu, Jason D. Lee
We study the implicit regularization imposed by gradient descent for learning multi-layer homogeneous functions including feed-forward fully connected and convolutional deep neural…
Online Improper Learning with an Approximation Oracle
Elad Hazan, Wei Hu, Yuanzhi Li +1
We revisit the question of reducing online learning to approximate optimization of the offline problem. In this setting, we give two algorithms with near-optimal performance in the…
An Analysis of the t-SNE Algorithm for Data Visualization
Sanjeev Arora, Wei Hu, Pravesh K. Kothari
A first line of attack in exploratory data analysis is data visualization, i.e., generating a 2-dimensional representation of data that makes clusters of similar points visually id…
Linear Convergence of the Primal-Dual Gradient Method for Convex-Concave Saddle Point Problems without Strong Convexity
Simon S. Du, Wei Hu
We consider the convex-concave saddle point problem where is smooth and convex and is smooth and strongly convex. We prove that if t…