Minnorm training: an algorithm for training over-parameterized deep
neural networks

Minnorm training: an algorithm for training over-parameterized deep neural networks

3 June 2018

Madhu S. Advani

Papers citing "Minnorm training: an algorithm for training over-parameterized deep neural networks"

18 / 18 papers shown

Title
Convergence of Gradient Descent on Separable Data Mor Shpigel Nacson Jason D. Lee Suriya Gunasekar Pedro H. P. Savarese Nathan Srebro Daniel Soudry 65 168 0 05 Mar 2018
Stronger generalization bounds for deep nets via a compression approach Sanjeev Arora Rong Ge Behnam Neyshabur Yi Zhang MLT AI4CE 84 639 0 14 Feb 2018
To understand deep learning we need to understand kernel learning M. Belkin Siyuan Ma Soumik Mandal 57 418 0 05 Feb 2018
The Implicit Bias of Gradient Descent on Separable Data Daniel Soudry Elad Hoffer Mor Shpigel Nacson Suriya Gunasekar Nathan Srebro 139 914 0 27 Oct 2017
SGD Learns Over-parameterized Networks that Provably Generalize on Linearly Separable Data Alon Brutzkus Amir Globerson Eran Malach Shai Shalev-Shwartz MLT 151 279 0 27 Oct 2017
High-dimensional dynamics of generalization error in neural networks Madhu S. Advani Andrew M. Saxe AI4CE 128 469 0 10 Oct 2017
A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks Behnam Neyshabur Srinadh Bhojanapalli Nathan Srebro 80 605 0 29 Jul 2017
Exploring Generalization in Deep Learning Behnam Neyshabur Srinadh Bhojanapalli David A. McAllester Nathan Srebro FAtt 141 1,251 0 27 Jun 2017
Spectrally-normalized margin bounds for neural networks Peter L. Bartlett Dylan J. Foster Matus Telgarsky ODL 187 1,216 0 26 Jun 2017
Computing Nonvacuous Generalization Bounds for Deep (Stochastic) Neural Networks with Many More Parameters than Training Data Gintare Karolina Dziugaite Daniel M. Roy 106 812 0 31 Mar 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 169 2,878 0 14 Mar 2017
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 320 4,624 0 10 Nov 2016
An Analysis of Deep Neural Network Models for Practical Applications A. Canziani Adam Paszke Eugenio Culurciello 85 1,167 0 24 May 2016
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He Xinming Zhang Shaoqing Ren Jian Sun VLM 286 18,587 0 06 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.5K 149,842 0 22 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.4K 100,213 0 04 Sep 2014
Exact solutions to the nonlinear dynamics of learning in deep linear neural networks Andrew M. Saxe James L. McClelland Surya Ganguli ODL 162 1,844 0 20 Dec 2013
Deep Learning using Linear Support Vector Machines Yichuan Tang 95 894 0 02 Jun 2013