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How regularization affects the critical points in linear networks

How regularization affects the critical points in linear networks

27 September 2017
Amirhossein Taghvaei
Jin-Won Kim
P. Mehta
ArXivPDFHTML

Papers citing "How regularization affects the critical points in linear networks"

15 / 15 papers shown
Title
Implicit Regularization in Matrix Factorization
Implicit Regularization in Matrix Factorization
Suriya Gunasekar
Blake E. Woodworth
Srinadh Bhojanapalli
Behnam Neyshabur
Nathan Srebro
52
490
0
25 May 2017
Identity Matters in Deep Learning
Identity Matters in Deep Learning
Moritz Hardt
Tengyu Ma
OOD
50
398
0
14 Nov 2016
Understanding deep learning requires rethinking generalization
Understanding deep learning requires rethinking generalization
Chiyuan Zhang
Samy Bengio
Moritz Hardt
Benjamin Recht
Oriol Vinyals
HAI
245
4,612
0
10 Nov 2016
Optimization Methods for Large-Scale Machine Learning
Optimization Methods for Large-Scale Machine Learning
Léon Bottou
Frank E. Curtis
J. Nocedal
168
3,191
0
15 Jun 2016
No bad local minima: Data independent training error guarantees for
  multilayer neural networks
No bad local minima: Data independent training error guarantees for multilayer neural networks
Daniel Soudry
Y. Carmon
99
235
0
26 May 2016
Global Optimality of Local Search for Low Rank Matrix Recovery
Global Optimality of Local Search for Low Rank Matrix Recovery
Srinadh Bhojanapalli
Behnam Neyshabur
Nathan Srebro
ODL
50
388
0
23 May 2016
Deep Learning without Poor Local Minima
Deep Learning without Poor Local Minima
Kenji Kawaguchi
ODL
130
919
0
23 May 2016
A Variational Perspective on Accelerated Methods in Optimization
A Variational Perspective on Accelerated Methods in Optimization
Andre Wibisono
Ashia Wilson
Michael I. Jordan
74
572
0
14 Mar 2016
Gradient Descent Converges to Minimizers
Gradient Descent Converges to Minimizers
Jason D. Lee
Max Simchowitz
Michael I. Jordan
Benjamin Recht
51
211
0
16 Feb 2016
Escaping From Saddle Points --- Online Stochastic Gradient for Tensor
  Decomposition
Escaping From Saddle Points --- Online Stochastic Gradient for Tensor Decomposition
Rong Ge
Furong Huang
Chi Jin
Yang Yuan
112
1,056
0
06 Mar 2015
A Differential Equation for Modeling Nesterov's Accelerated Gradient
  Method: Theory and Insights
A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights
Weijie Su
Stephen P. Boyd
Emmanuel J. Candes
149
1,161
0
04 Mar 2015
In Search of the Real Inductive Bias: On the Role of Implicit
  Regularization in Deep Learning
In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning
Behnam Neyshabur
Ryota Tomioka
Nathan Srebro
AI4CE
58
655
0
20 Dec 2014
The Loss Surfaces of Multilayer Networks
The Loss Surfaces of Multilayer Networks
A. Choromańska
Mikael Henaff
Michaël Mathieu
Gerard Ben Arous
Yann LeCun
ODL
223
1,189
0
30 Nov 2014
Identifying and attacking the saddle point problem in high-dimensional
  non-convex optimization
Identifying and attacking the saddle point problem in high-dimensional non-convex optimization
Yann N. Dauphin
Razvan Pascanu
Çağlar Gülçehre
Kyunghyun Cho
Surya Ganguli
Yoshua Bengio
ODL
92
1,379
0
10 Jun 2014
Exact solutions to the nonlinear dynamics of learning in deep linear
  neural networks
Exact solutions to the nonlinear dynamics of learning in deep linear neural networks
Andrew M. Saxe
James L. McClelland
Surya Ganguli
ODL
93
1,830
0
20 Dec 2013
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