The Multilinear Structure of ReLU Networks

29 December 2017

Papers citing "The Multilinear Structure of ReLU Networks"

12 / 12 papers shown

Title
GD doesn't make the cut: Three ways that non-differentiability affects neural network training Siddharth Krishna Kumar AAML 26 2 0 16 Jan 2024
On the Correctness of Automatic Differentiation for Neural Networks with Machine-Representable Parameters Wonyeol Lee Sejun Park A. Aiken PINN 21 6 0 31 Jan 2023
Parametric Flatten-T Swish: An Adaptive Non-linear Activation Function For Deep Learning Hock Hung Chieng Noorhaniza Wahid P. Ong 21 6 0 06 Nov 2020
Critical Point-Finding Methods Reveal Gradient-Flat Regions of Deep Network Losses Charles G. Frye James B. Simon Neha S. Wadia A. Ligeralde M. DeWeese K. Bouchard ODL 16 2 0 23 Mar 2020
Revisiting Landscape Analysis in Deep Neural Networks: Eliminating Decreasing Paths to Infinity Shiyu Liang Ruoyu Sun R. Srikant 35 19 0 31 Dec 2019
Optimization for deep learning: theory and algorithms Ruoyu Sun ODL 25 168 0 19 Dec 2019
Non-attracting Regions of Local Minima in Deep and Wide Neural Networks Henning Petzka C. Sminchisescu 29 9 0 16 Dec 2018
Subgradient Descent Learns Orthogonal Dictionaries Yu Bai Qijia Jiang Ju Sun 20 51 0 25 Oct 2018
Learning ReLU Networks on Linearly Separable Data: Algorithm, Optimality, and Generalization G. Wang G. Giannakis Jie Chen MLT 24 131 0 14 Aug 2018
Deep Neural Networks with Multi-Branch Architectures Are Less Non-Convex Hongyang R. Zhang Junru Shao Ruslan Salakhutdinov 39 14 0 06 Jun 2018
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 308 2,892 0 15 Sep 2016
The Loss Surfaces of Multilayer Networks A. Choromańska Mikael Henaff Michaël Mathieu Gerard Ben Arous Yann LeCun ODL 183 1,185 0 30 Nov 2014