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Global Optimality in Tensor Factorization, Deep Learning, and Beyond

Global Optimality in Tensor Factorization, Deep Learning, and Beyond

24 June 2015
B. Haeffele
René Vidal
ArXiv (abs)PDFHTML

Papers citing "Global Optimality in Tensor Factorization, Deep Learning, and Beyond"

33 / 83 papers shown
Title
On the Optimization of Deep Networks: Implicit Acceleration by
  Overparameterization
On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization
Sanjeev Arora
Nadav Cohen
Elad Hazan
129
488
0
19 Feb 2018
Understanding the Loss Surface of Neural Networks for Binary
  Classification
Understanding the Loss Surface of Neural Networks for Binary Classification
Shiyu Liang
Ruoyu Sun
Yixuan Li
R. Srikant
95
88
0
19 Feb 2018
Robust Kronecker Component Analysis
Robust Kronecker Component Analysis
Mehdi Bahri
Yannis Panagakis
Stefanos Zafeiriou
83
29
0
18 Jan 2018
Spurious Local Minima are Common in Two-Layer ReLU Neural Networks
Spurious Local Minima are Common in Two-Layer ReLU Neural Networks
Itay Safran
Ohad Shamir
186
265
0
24 Dec 2017
Mathematics of Deep Learning
Mathematics of Deep Learning
René Vidal
Joan Bruna
Raja Giryes
Stefano Soatto
OOD
65
120
0
13 Dec 2017
Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of
  Spurious Local Minima
Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima
S. Du
Jason D. Lee
Yuandong Tian
Barnabás Póczós
Aarti Singh
MLT
160
236
0
03 Dec 2017
Optimization Landscape and Expressivity of Deep CNNs
Optimization Landscape and Expressivity of Deep CNNs
Quynh N. Nguyen
Matthias Hein
101
29
0
30 Oct 2017
Dropout as a Low-Rank Regularizer for Matrix Factorization
Dropout as a Low-Rank Regularizer for Matrix Factorization
Jacopo Cavazza
Pietro Morerio
B. Haeffele
Connor Lane
Vittorio Murino
René Vidal
126
42
0
13 Oct 2017
When is a Convolutional Filter Easy To Learn?
When is a Convolutional Filter Easy To Learn?
S. Du
Jason D. Lee
Yuandong Tian
MLT
62
130
0
18 Sep 2017
Newton-Type Methods for Non-Convex Optimization Under Inexact Hessian
  Information
Newton-Type Methods for Non-Convex Optimization Under Inexact Hessian Information
Peng Xu
Farbod Roosta-Khorasani
Michael W. Mahoney
131
214
0
23 Aug 2017
Learning Sparse Representations in Reinforcement Learning with Sparse
  Coding
Learning Sparse Representations in Reinforcement Learning with Sparse Coding
Lei Le
Raksha Kumaraswamy
Martha White
OffRLSSL
60
25
0
26 Jul 2017
Tensor Regression Networks
Tensor Regression Networks
Jean Kossaifi
Zachary Chase Lipton
Arinbjorn Kolbeinsson
Aran Khanna
Tommaso Furlanello
Anima Anandkumar
3DV
114
148
0
26 Jul 2017
Theoretical insights into the optimization landscape of
  over-parameterized shallow neural networks
Theoretical insights into the optimization landscape of over-parameterized shallow neural networks
Mahdi Soltanolkotabi
Adel Javanmard
Jason D. Lee
201
423
0
16 Jul 2017
Reexamining Low Rank Matrix Factorization for Trace Norm Regularization
Reexamining Low Rank Matrix Factorization for Trace Norm Regularization
C. Ciliberto
Dimitris Stamos
Massimiliano Pontil
102
10
0
27 Jun 2017
Recovery Guarantees for One-hidden-layer Neural Networks
Recovery Guarantees for One-hidden-layer Neural Networks
Kai Zhong
Zhao Song
Prateek Jain
Peter L. Bartlett
Inderjit S. Dhillon
MLT
186
337
0
10 Jun 2017
The loss surface of deep and wide neural networks
The loss surface of deep and wide neural networks
Quynh N. Nguyen
Matthias Hein
ODL
188
285
0
26 Apr 2017
Deep Relaxation: partial differential equations for optimizing deep
  neural networks
Deep Relaxation: partial differential equations for optimizing deep neural networks
Pratik Chaudhari
Adam M. Oberman
Stanley Osher
Stefano Soatto
G. Carlier
163
154
0
17 Apr 2017
Robust Kronecker-Decomposable Component Analysis for Low-Rank Modeling
Robust Kronecker-Decomposable Component Analysis for Low-Rank Modeling
Mehdi Bahri
Yannis Panagakis
Stefanos Zafeiriou
74
14
0
22 Mar 2017
Curriculum Dropout
Curriculum Dropout
Pietro Morerio
Jacopo Cavazza
Riccardo Volpi
René Vidal
Vittorio Murino
ODL
140
106
0
18 Mar 2017
Depth Creates No Bad Local Minima
Depth Creates No Bad Local Minima
Haihao Lu
Kenji Kawaguchi
ODLFAtt
102
121
0
27 Feb 2017
Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs
Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs
Alon Brutzkus
Amir Globerson
MLT
182
313
0
26 Feb 2017
How ConvNets model Non-linear Transformations
How ConvNets model Non-linear Transformations
Dipan K. Pal
Marios Savvides
102
0
0
24 Feb 2017
Entropy-SGD: Biasing Gradient Descent Into Wide Valleys
Entropy-SGD: Biasing Gradient Descent Into Wide Valleys
Pratik Chaudhari
A. Choromańska
Stefano Soatto
Yann LeCun
Carlo Baldassi
C. Borgs
J. Chayes
Levent Sagun
R. Zecchina
ODL
108
775
0
06 Nov 2016
Understanding Deep Neural Networks with Rectified Linear Units
Understanding Deep Neural Networks with Rectified Linear Units
R. Arora
A. Basu
Poorya Mianjy
Anirbit Mukherjee
PINN
206
644
0
04 Nov 2016
Globally Optimal Training of Generalized Polynomial Neural Networks with
  Nonlinear Spectral Methods
Globally Optimal Training of Generalized Polynomial Neural Networks with Nonlinear Spectral Methods
A. Gautier
Quynh N. Nguyen
Matthias Hein
131
32
0
28 Oct 2016
Master's Thesis : Deep Learning for Visual Recognition
Master's Thesis : Deep Learning for Visual Recognition
Rémi Cadène
Nicolas Thome
Matthieu Cord
119
4
0
18 Oct 2016
Convexified Convolutional Neural Networks
Convexified Convolutional Neural Networks
Yuchen Zhang
Percy Liang
Martin J. Wainwright
168
65
0
04 Sep 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
214
236
0
26 May 2016
Robust Large Margin Deep Neural Networks
Robust Large Margin Deep Neural Networks
Jure Sokolić
Raja Giryes
Guillermo Sapiro
M. Rodrigues
86
309
0
26 May 2016
Unconstrained Still/Video-Based Face Verification with Deep
  Convolutional Neural Networks
Unconstrained Still/Video-Based Face Verification with Deep Convolutional Neural Networks
Jun-Cheng Chen
Rajeev Ranjan
Swami Sankaranarayanan
Amit Kumar
Ching-Hui Chen
Vishal M. Patel
Carlos D. Castillo
Rama Chellappa
CVBM
100
97
0
09 May 2016
On the energy landscape of deep networks
On the energy landscape of deep networks
Pratik Chaudhari
Stefano Soatto
ODL
92
27
0
20 Nov 2015
On the Quality of the Initial Basin in Overspecified Neural Networks
On the Quality of the Initial Basin in Overspecified Neural Networks
Itay Safran
Ohad Shamir
99
127
0
13 Nov 2015
On the Expressive Power of Deep Learning: A Tensor Analysis
On the Expressive Power of Deep Learning: A Tensor Analysis
Nadav Cohen
Or Sharir
Amnon Shashua
91
472
0
16 Sep 2015
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