Beating the Perils of Non-Convexity: Guaranteed Training of Neural Networks using Tensor Methods

28 June 2015

Papers citing "Beating the Perils of Non-Convexity: Guaranteed Training of Neural Networks using Tensor Methods"

7 / 7 papers shown

Title
Marginalizable Density Models D. Gilboa Ari Pakman Thibault Vatter BDL 32 5 0 08 Jun 2021
Gradient Descent for One-Hidden-Layer Neural Networks: Polynomial Convergence and SQ Lower Bounds Santosh Vempala John Wilmes MLT 13 50 0 07 May 2018
Tensor Regression Networks Jean Kossaifi Zachary Chase Lipton Arinbjorn Kolbeinsson Aran Khanna Tommaso Furlanello Anima Anandkumar 3DV 43 145 0 26 Jul 2017
Convergence Results for Neural Networks via Electrodynamics Rina Panigrahy Sushant Sachdeva Qiuyi Zhang MLT MDE 29 22 0 01 Feb 2017
Convexified Convolutional Neural Networks Yuchen Zhang Percy Liang Martin J. Wainwright 26 64 0 04 Sep 2016
AdaNet: Adaptive Structural Learning of Artificial Neural Networks Corinna Cortes X. Gonzalvo Vitaly Kuznetsov M. Mohri Scott Yang 29 282 0 05 Jul 2016
$$\ell_1$-regularized Neural Networks are Improperly Learnable in Polynomial Time$ $\ell_1$ -regularized Neural Networks are Improperly Learnable in Polynomial Time Yuchen Zhang J. Lee Michael I. Jordan 24 101 0 13 Oct 2015