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Explorations on high dimensional landscapes
International Conference on Learning Representations (ICLR), 2014
20 December 2014
Levent Sagun
V. U. Güney
Gerard Ben Arous
Yann LeCun
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Papers citing
"Explorations on high dimensional landscapes"
41 / 41 papers shown
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A survey of deep learning optimizers -- first and second order methods
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28 Nov 2022
A Local Optima Network Analysis of the Feedforward Neural Architecture Space
IEEE International Joint Conference on Neural Network (IJCNN), 2022
Isak Potgieter
C. Cleghorn
Anna Sergeevna Bosman
106
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0
02 Jun 2022
Universal characteristics of deep neural network loss surfaces from random matrix theory
Nicholas P. Baskerville
J. Keating
F. Mezzadri
J. Najnudel
Diego Granziol
196
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17 May 2022
Exponentially Many Local Minima in Quantum Neural Networks
Xuchen You
Xiaodi Wu
305
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06 Oct 2021
Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances
International Conference on Machine Learning (ICML), 2021
Berfin cSimcsek
François Ged
Arthur Jacot
Francesco Spadaro
Clément Hongler
W. Gerstner
Johanni Brea
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297
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0
25 May 2021
Appearance of Random Matrix Theory in Deep Learning
Nicholas P. Baskerville
Diego Granziol
J. Keating
382
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0
12 Feb 2021
Algebraically-Informed Deep Networks (AIDN): A Deep Learning Approach to Represent Algebraic Structures
Pavlo Vasylenko
Ghada Zamzmi
Matthew Dawson
G. Muller
249
3
0
02 Dec 2020
Optimizing Mode Connectivity via Neuron Alignment
Neural Information Processing Systems (NeurIPS), 2020
N. Joseph Tatro
Pin-Yu Chen
Payel Das
Igor Melnyk
P. Sattigeri
Rongjie Lai
MoMe
681
93
0
05 Sep 2020
A Topological Framework for Deep Learning
Pavlo Vasylenko
Kyle Istvan
854
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31 Aug 2020
Error Estimation and Correction from within Neural Network Differential Equation Solvers
Akshunna S. Dogra
162
1
0
09 Jul 2020
The Loss Surfaces of Neural Networks with General Activation Functions
Journal of Statistical Mechanics: Theory and Experiment (JSTAT), 2020
Nicholas P. Baskerville
J. Keating
F. Mezzadri
J. Najnudel
ODL
AI4CE
361
28
0
08 Apr 2020
On the Heavy-Tailed Theory of Stochastic Gradient Descent for Deep Neural Networks
Umut Simsekli
Mert Gurbuzbalaban
T. H. Nguyen
G. Richard
Levent Sagun
309
64
0
29 Nov 2019
Who is Afraid of Big Bad Minima? Analysis of Gradient-Flow in a Spiked Matrix-Tensor Model
Neural Information Processing Systems (NeurIPS), 2019
Stefano Sarao Mannelli
Giulio Biroli
C. Cammarota
Florent Krzakala
Lenka Zdeborová
175
46
0
18 Jul 2019
Weight-space symmetry in deep networks gives rise to permutation saddles, connected by equal-loss valleys across the loss landscape
Johanni Brea
Berfin Simsek
Bernd Illing
W. Gerstner
287
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0
05 Jul 2019
The Difficulty of Training Sparse Neural Networks
Utku Evci
Fabian Pedregosa
Aidan Gomez
Erich Elsen
336
106
0
25 Jun 2019
Loss Surface Modality of Feed-Forward Neural Network Architectures
IEEE International Joint Conference on Neural Network (IJCNN), 2019
Anna Sergeevna Bosman
A. Engelbrecht
Mardé Helbig
188
10
0
24 May 2019
A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks
Umut Simsekli
Levent Sagun
Mert Gurbuzbalaban
488
288
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18 Jan 2019
Marvels and Pitfalls of the Langevin Algorithm in Noisy High-dimensional Inference
Stefano Sarao Mannelli
Giulio Biroli
C. Cammarota
Florent Krzakala
Pierfrancesco Urbani
Lenka Zdeborová
422
48
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21 Dec 2018
Non-attracting Regions of Local Minima in Deep and Wide Neural Networks
Henning Petzka
C. Sminchisescu
247
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16 Dec 2018
Intrinsic Geometric Vulnerability of High-Dimensional Artificial Intelligence
Luca Bortolussi
G. Sanguinetti
AAML
211
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08 Nov 2018
The loss surface of deep linear networks viewed through the algebraic geometry lens
D. Mehta
Tianran Chen
Tingting Tang
J. Hauenstein
ODL
233
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17 Oct 2018
Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning
Charles H. Martin
Michael W. Mahoney
AI4CE
369
234
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02 Oct 2018
Trust-Region Algorithms for Training Responses: Machine Learning Methods Using Indefinite Hessian Approximations
Jennifer B. Erway
J. Griffin
Roummel F. Marcia
Riadh Omheni
333
26
0
01 Jul 2018
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
267
112
0
14 Jun 2018
Input and Weight Space Smoothing for Semi-supervised Learning
Safa Cicek
Stefano Soatto
115
6
0
23 May 2018
Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach
Grant M. Rotskoff
Eric Vanden-Eijnden
335
140
0
02 May 2018
The Loss Surface of XOR Artificial Neural Networks
D. Mehta
Xiaojun Zhao
Edgar A. Bernal
D. Wales
256
19
0
06 Apr 2018
Comparing Dynamics: Deep Neural Networks versus Glassy Systems
Carlo Albert
Levent Sagun
Mario Geiger
S. Spigler
Gerard Ben Arous
C. Cammarota
Yann LeCun
Matthieu Wyart
Giulio Biroli
AI4CE
318
124
0
19 Mar 2018
Rethinking generalization requires revisiting old ideas: statistical mechanics approaches and complex learning behavior
Charles H. Martin
Michael W. Mahoney
AI4CE
182
64
0
26 Oct 2017
Deep Learning applied to Road Traffic Speed forecasting
T. Epelbaum
Fabrice Gamboa
Jean-Michel Loubes
J. Martin
AI4TS
173
11
0
02 Oct 2017
Empirical Analysis of the Hessian of Over-Parametrized Neural Networks
International Conference on Learning Representations (ICLR), 2017
Levent Sagun
Utku Evci
V. U. Güney
Yann N. Dauphin
Léon Bottou
338
444
0
14 Jun 2017
Sharp Minima Can Generalize For Deep Nets
Laurent Dinh
Razvan Pascanu
Samy Bengio
Yoshua Bengio
ODL
414
832
0
15 Mar 2017
Eigenvalues of the Hessian in Deep Learning: Singularity and Beyond
Levent Sagun
Léon Bottou
Yann LeCun
UQCV
283
257
0
22 Nov 2016
Local minima in training of neural networks
G. Swirszcz
Wojciech M. Czarnecki
Razvan Pascanu
ODL
190
78
0
19 Nov 2016
Topology and Geometry of Half-Rectified Network Optimization
C. Freeman
Joan Bruna
735
240
0
04 Nov 2016
On the Modeling of Error Functions as High Dimensional Landscapes for Weight Initialization in Learning Networks
Julius
Gopinath Mahale
Sumana T
C. S. Adityakrishna
96
1
0
20 Jul 2016
AdaNet: Adaptive Structural Learning of Artificial Neural Networks
International Conference on Machine Learning (ICML), 2016
Corinna Cortes
X. Gonzalvo
Vitaly Kuznetsov
M. Mohri
Scott Yang
335
294
0
05 Jul 2016
On the energy landscape of deep networks
Pratik Chaudhari
Stefano Soatto
ODL
323
27
0
20 Nov 2015
Universal halting times in optimization and machine learning
Levent Sagun
T. Trogdon
Yann LeCun
BDL
138
9
0
19 Nov 2015
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