Convergence and Implicit Bias of Gradient Flow on Overparametrized Linear Networks

13 May 2021

Papers citing "Convergence and Implicit Bias of Gradient Flow on Overparametrized Linear Networks"

8 / 8 papers shown

Title
A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Ziqing Xu Hancheng Min Salma Tarmoun Enrique Mallada Rene Vidal 78 0 0 16 May 2025
Deep Networks and the Multiple Manifold Problem Sam Buchanan D. Gilboa John N. Wright 171 39 0 25 Aug 2020
Gradient Descent Maximizes the Margin of Homogeneous Neural Networks Kaifeng Lyu Jian Li 68 332 0 13 Jun 2019
Implicit Regularization in Deep Matrix Factorization Sanjeev Arora Nadav Cohen Wei Hu Yuping Luo AI4CE 64 500 0 31 May 2019
Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks Yuan Cao Quanquan Gu MLT AI4CE 68 384 0 30 May 2019
Width Provably Matters in Optimization for Deep Linear Neural Networks S. Du Wei Hu 55 94 0 24 Jan 2019
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers Zeyuan Allen-Zhu Yuanzhi Li Yingyu Liang MLT 136 769 0 12 Nov 2018
Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data Yuanzhi Li Yingyu Liang MLT 140 652 0 03 Aug 2018