Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path?

25 December 2018

Papers citing "Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path?"

10 / 60 papers shown

Title
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark Schmidt 280 1,222 0 16 Aug 2016
TensorFlow: A system for large-scale machine learning Martín Abadi P. Barham Jianmin Chen Zhiwen Chen Andy Davis ... Vijay Vasudevan Pete Warden Martin Wicke Yuan Yu Xiaoqiang Zhang GNN AI4CE 435 18,361 0 27 May 2016
No bad local minima: Data independent training error guarantees for multilayer neural networks Daniel Soudry Y. Carmon 209 236 0 26 May 2016
Global Optimality of Local Search for Low Rank Matrix Recovery Srinadh Bhojanapalli Behnam Neyshabur Nathan Srebro ODL 132 388 0 23 May 2016
A Geometric Analysis of Phase Retrieval Ju Sun Qing Qu John N. Wright 134 526 0 22 Feb 2016
Sharp Time--Data Tradeoffs for Linear Inverse Problems Samet Oymak Benjamin Recht Mahdi Soltanolkotabi 85 89 0 16 Jul 2015
Taming the Wild: A Unified Analysis of Hogwild!-Style Algorithms Christopher De Sa Ce Zhang K. Olukotun Christopher Ré 97 204 0 22 Jun 2015
In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning Behnam Neyshabur Ryota Tomioka Nathan Srebro AI4CE 106 663 0 20 Dec 2014
Phase Retrieval via Wirtinger Flow: Theory and Algorithms Emmanuel Candes Xiaodong Li Mahdi Soltanolkotabi 199 1,291 0 03 Jul 2014
Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization Alexander Rakhlin Ohad Shamir Karthik Sridharan 188 769 0 26 Sep 2011