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Analytic Study of Families of Spurious Minima in Two-Layer ReLU Neural
  Networks: A Tale of Symmetry II

Analytic Study of Families of Spurious Minima in Two-Layer ReLU Neural Networks: A Tale of Symmetry II

21 July 2021
Yossi Arjevani
M. Field
ArXivPDFHTML

Papers citing "Analytic Study of Families of Spurious Minima in Two-Layer ReLU Neural Networks: A Tale of Symmetry II"

41 / 41 papers shown
Title
Learning Gaussian Multi-Index Models with Gradient Flow: Time Complexity and Directional Convergence
Learning Gaussian Multi-Index Models with Gradient Flow: Time Complexity and Directional Convergence
Berfin Simsek
Amire Bendjeddou
Daniel Hsu
104
0
0
13 Nov 2024
Loss Landscape of Shallow ReLU-like Neural Networks: Stationary Points, Saddle Escape, and Network Embedding
Loss Landscape of Shallow ReLU-like Neural Networks: Stationary Points, Saddle Escape, and Network Embedding
Zhengqing Wu
Berfin Simsek
Francois Ged
ODL
64
0
0
08 Feb 2024
Symmetry & Critical Points for Symmetric Tensor Decomposition Problems
Symmetry & Critical Points for Symmetric Tensor Decomposition Problems
Yossi Arjevani
Gal Vinograd
49
5
0
13 Jun 2023
Equivariant bifurcation, quadratic equivariants, and symmetry breaking
  for the standard representation of $S_n$
Equivariant bifurcation, quadratic equivariants, and symmetry breaking for the standard representation of SnS_nSn​
Yossi Arjevani
M. Field
45
8
0
06 Jul 2021
On Learnability via Gradient Method for Two-Layer ReLU Neural Networks
  in Teacher-Student Setting
On Learnability via Gradient Method for Two-Layer ReLU Neural Networks in Teacher-Student Setting
Shunta Akiyama
Taiji Suzuki
MLT
100
13
0
11 Jun 2021
Symmetry Breaking in Symmetric Tensor Decomposition
Symmetry Breaking in Symmetric Tensor Decomposition
Yossi Arjevani
Joan Bruna
M. Field
Joe Kileel
Matthew Trager
Francis Williams
49
8
0
10 Mar 2021
Nonparametric Learning of Two-Layer ReLU Residual Units
Nonparametric Learning of Two-Layer ReLU Residual Units
Zhunxuan Wang
Linyun He
Chunchuan Lyu
Shay B. Cohen
MLT
OffRL
97
1
0
17 Aug 2020
Analytic Characterization of the Hessian in Shallow ReLU Models: A Tale
  of Symmetry
Analytic Characterization of the Hessian in Shallow ReLU Models: A Tale of Symmetry
Yossi Arjevani
M. Field
30
16
0
04 Aug 2020
Optimization and Generalization of Shallow Neural Networks with
  Quadratic Activation Functions
Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions
Stefano Sarao Mannelli
Eric Vanden-Eijnden
Lenka Zdeborová
AI4CE
21
46
0
27 Jun 2020
When Do Neural Networks Outperform Kernel Methods?
When Do Neural Networks Outperform Kernel Methods?
Behrooz Ghorbani
Song Mei
Theodor Misiakiewicz
Andrea Montanari
74
188
0
24 Jun 2020
Symmetry & critical points for a model shallow neural network
Symmetry & critical points for a model shallow neural network
Yossi Arjevani
M. Field
55
13
0
23 Mar 2020
On the Principle of Least Symmetry Breaking in Shallow ReLU Models
On the Principle of Least Symmetry Breaking in Shallow ReLU Models
Yossi Arjevani
M. Field
46
7
0
26 Dec 2019
Hidden Unit Specialization in Layered Neural Networks: ReLU vs.
  Sigmoidal Activation
Hidden Unit Specialization in Layered Neural Networks: ReLU vs. Sigmoidal Activation
Elisa Oostwal
Michiel Straat
Michael Biehl
MLT
73
56
0
16 Oct 2019
Dynamics of stochastic gradient descent for two-layer neural networks in
  the teacher-student setup
Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup
Sebastian Goldt
Madhu S. Advani
Andrew M. Saxe
Florent Krzakala
Lenka Zdeborová
MLT
91
142
0
18 Jun 2019
On the Power and Limitations of Random Features for Understanding Neural
  Networks
On the Power and Limitations of Random Features for Understanding Neural Networks
Gilad Yehudai
Ohad Shamir
MLT
49
182
0
01 Apr 2019
An Investigation into Neural Net Optimization via Hessian Eigenvalue
  Density
An Investigation into Neural Net Optimization via Hessian Eigenvalue Density
Behrooz Ghorbani
Shankar Krishnan
Ying Xiao
ODL
36
320
0
29 Jan 2019
Generalisation dynamics of online learning in over-parameterised neural
  networks
Generalisation dynamics of online learning in over-parameterised neural networks
Sebastian Goldt
Madhu S. Advani
Andrew M. Saxe
Florent Krzakala
Lenka Zdeborová
37
14
0
25 Jan 2019
Gradient Descent Happens in a Tiny Subspace
Gradient Descent Happens in a Tiny Subspace
Guy Gur-Ari
Daniel A. Roberts
Ethan Dyer
59
232
0
12 Dec 2018
The committee machine: Computational to statistical gaps in learning a
  two-layers neural network
The committee machine: Computational to statistical gaps in learning a two-layers neural network
Benjamin Aubin
Antoine Maillard
Jean Barbier
Florent Krzakala
N. Macris
Lenka Zdeborová
60
105
0
14 Jun 2018
Universal Statistics of Fisher Information in Deep Neural Networks: Mean
  Field Approach
Universal Statistics of Fisher Information in Deep Neural Networks: Mean Field Approach
Ryo Karakida
S. Akaho
S. Amari
FedML
106
142
0
04 Jun 2018
On the Global Convergence of Gradient Descent for Over-parameterized
  Models using Optimal Transport
On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport
Lénaïc Chizat
Francis R. Bach
OT
150
731
0
24 May 2018
Measuring the Intrinsic Dimension of Objective Landscapes
Measuring the Intrinsic Dimension of Objective Landscapes
Chunyuan Li
Heerad Farkhoor
Rosanne Liu
J. Yosinski
66
407
0
24 Apr 2018
A Mean Field View of the Landscape of Two-Layers Neural Networks
A Mean Field View of the Landscape of Two-Layers Neural Networks
Song Mei
Andrea Montanari
Phan-Minh Nguyen
MLT
69
855
0
18 Apr 2018
Hessian-based Analysis of Large Batch Training and Robustness to
  Adversaries
Hessian-based Analysis of Large Batch Training and Robustness to Adversaries
Z. Yao
A. Gholami
Qi Lei
Kurt Keutzer
Michael W. Mahoney
51
166
0
22 Feb 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
112
263
0
24 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
120
236
0
03 Dec 2017
Three Factors Influencing Minima in SGD
Three Factors Influencing Minima in SGD
Stanislaw Jastrzebski
Zachary Kenton
Devansh Arpit
Nicolas Ballas
Asja Fischer
Yoshua Bengio
Amos Storkey
67
458
0
13 Nov 2017
Learning One-hidden-layer Neural Networks with Landscape Design
Learning One-hidden-layer Neural Networks with Landscape Design
Rong Ge
Jason D. Lee
Tengyu Ma
MLT
117
260
0
01 Nov 2017
Porcupine Neural Networks: (Almost) All Local Optima are Global
Porcupine Neural Networks: (Almost) All Local Optima are Global
Soheil Feizi
Hamid Javadi
Jesse M. Zhang
David Tse
62
36
0
05 Oct 2017
Towards Understanding Generalization of Deep Learning: Perspective of
  Loss Landscapes
Towards Understanding Generalization of Deep Learning: Perspective of Loss Landscapes
Lei Wu
Zhanxing Zhu
E. Weinan
ODL
48
220
0
30 Jun 2017
Empirical Analysis of the Hessian of Over-Parametrized Neural Networks
Empirical Analysis of the Hessian of Over-Parametrized Neural Networks
Levent Sagun
Utku Evci
V. U. Güney
Yann N. Dauphin
Léon Bottou
39
415
0
14 Jun 2017
Convergence Analysis of Two-layer Neural Networks with ReLU Activation
Convergence Analysis of Two-layer Neural Networks with ReLU Activation
Yuanzhi Li
Yang Yuan
MLT
80
649
0
28 May 2017
Sharp Minima Can Generalize For Deep Nets
Sharp Minima Can Generalize For Deep Nets
Laurent Dinh
Razvan Pascanu
Samy Bengio
Yoshua Bengio
ODL
98
763
0
15 Mar 2017
An Analytical Formula of Population Gradient for two-layered ReLU
  network and its Applications in Convergence and Critical Point Analysis
An Analytical Formula of Population Gradient for two-layered ReLU network and its Applications in Convergence and Critical Point Analysis
Yuandong Tian
MLT
109
216
0
02 Mar 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
92
313
0
26 Feb 2017
A Random Matrix Approach to Neural Networks
A Random Matrix Approach to Neural Networks
Cosme Louart
Zhenyu Liao
Romain Couillet
41
161
0
17 Feb 2017
Eigenvalues of the Hessian in Deep Learning: Singularity and Beyond
Eigenvalues of the Hessian in Deep Learning: Singularity and Beyond
Levent Sagun
Léon Bottou
Yann LeCun
UQCV
69
233
0
22 Nov 2016
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
82
769
0
06 Nov 2016
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp
  Minima
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
353
2,913
0
15 Sep 2016
Distribution-Specific Hardness of Learning Neural Networks
Distribution-Specific Hardness of Learning Neural Networks
Ohad Shamir
52
116
0
05 Sep 2016
Toward Deeper Understanding of Neural Networks: The Power of
  Initialization and a Dual View on Expressivity
Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity
Amit Daniely
Roy Frostig
Y. Singer
85
343
0
18 Feb 2016
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