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Deep Neural Networks with Random Gaussian Weights: A Universal
  Classification Strategy?

Deep Neural Networks with Random Gaussian Weights: A Universal Classification Strategy?

30 April 2015
Raja Giryes
Guillermo Sapiro
A. Bronstein
ArXivPDFHTML

Papers citing "Deep Neural Networks with Random Gaussian Weights: A Universal Classification Strategy?"

32 / 32 papers shown
Title
Emergence of Structure in Ensembles of Random Neural Networks
Emergence of Structure in Ensembles of Random Neural Networks
Luca Muscarnera
Luigi Loreti
Giovanni Todeschini
Alessio Fumagalli
Francesco Regazzoni
26
0
0
15 May 2025
Neural Redshift: Random Networks are not Random Functions
Neural Redshift: Random Networks are not Random Functions
Damien Teney
A. Nicolicioiu
Valentin Hartmann
Ehsan Abbasnejad
103
18
0
04 Mar 2024
DataDAM: Efficient Dataset Distillation with Attention Matching
DataDAM: Efficient Dataset Distillation with Attention Matching
A. Sajedi
Samir Khaki
Ehsan Amjadian
Lucy Z. Liu
Y. Lawryshyn
Konstantinos N. Plataniotis
DD
46
59
0
29 Sep 2023
Neural Collapse: A Review on Modelling Principles and Generalization
Neural Collapse: A Review on Modelling Principles and Generalization
Vignesh Kothapalli
23
71
0
08 Jun 2022
Privacy for Free: How does Dataset Condensation Help Privacy?
Privacy for Free: How does Dataset Condensation Help Privacy?
Tian Dong
Bo-Lu Zhao
Lingjuan Lyu
DD
24
113
0
01 Jun 2022
Constructing coarse-scale bifurcation diagrams from spatio-temporal
  observations of microscopic simulations: A parsimonious machine learning
  approach
Constructing coarse-scale bifurcation diagrams from spatio-temporal observations of microscopic simulations: A parsimonious machine learning approach
Evangelos Galaris
Gianluca Fabiani
I. Gallos
Ioannis G. Kevrekidis
Constantinos Siettos
AI4CE
23
40
0
31 Jan 2022
Weighting and Pruning based Ensemble Deep Random Vector Functional Link
  Network for Tabular Data Classification
Weighting and Pruning based Ensemble Deep Random Vector Functional Link Network for Tabular Data Classification
Qi-Shi Shi
Ponnuthurai Nagaratnam Suganthan
Rakesh Katuwal
6
22
0
15 Jan 2022
Causality-inspired Single-source Domain Generalization for Medical Image
  Segmentation
Causality-inspired Single-source Domain Generalization for Medical Image Segmentation
Cheng Ouyang
C. L. P. Chen
Surui Li
Zeju Li
C. Qin
Wenjia Bai
Daniel Rueckert
OOD
30
155
0
24 Nov 2021
A Johnson--Lindenstrauss Framework for Randomly Initialized CNNs
A Johnson--Lindenstrauss Framework for Randomly Initialized CNNs
Ido Nachum
Jan Hkazla
Michael C. Gastpar
Anatoly Khina
36
0
0
03 Nov 2021
Efficient and Private Federated Learning with Partially Trainable
  Networks
Efficient and Private Federated Learning with Partially Trainable Networks
Hakim Sidahmed
Zheng Xu
Ankush Garg
Yuan Cao
Mingqing Chen
FedML
49
13
0
06 Oct 2021
Deep ReLU Networks Preserve Expected Length
Deep ReLU Networks Preserve Expected Length
Boris Hanin
Ryan Jeong
David Rolnick
23
14
0
21 Feb 2021
Reservoir Transformers
Reservoir Transformers
Sheng Shen
Alexei Baevski
Ari S. Morcos
Kurt Keutzer
Michael Auli
Douwe Kiela
35
17
0
30 Dec 2020
On Random Matrices Arising in Deep Neural Networks: General I.I.D. Case
On Random Matrices Arising in Deep Neural Networks: General I.I.D. Case
L. Pastur
V. Slavin
CML
24
12
0
20 Nov 2020
Untangling in Invariant Speech Recognition
Untangling in Invariant Speech Recognition
Cory Stephenson
J. Feather
Suchismita Padhy
Oguz H. Elibol
Hanlin Tang
Josh H. McDermott
SueYeon Chung
SSL
16
30
0
03 Mar 2020
Deep Randomized Neural Networks
Deep Randomized Neural Networks
Claudio Gallicchio
Simone Scardapane
OOD
41
61
0
27 Feb 2020
Deep Divergence-Based Approach to Clustering
Deep Divergence-Based Approach to Clustering
Michael C. Kampffmeyer
Sigurd Løkse
F. Bianchi
L. Livi
Arnt-Børre Salberg
Robert Jenssen
28
61
0
13 Feb 2019
On the security relevance of weights in deep learning
On the security relevance of weights in deep learning
Kathrin Grosse
T. A. Trost
Marius Mosbach
Michael Backes
Dietrich Klakow
AAML
32
6
0
08 Feb 2019
Deep Learning on Graphs: A Survey
Deep Learning on Graphs: A Survey
Ziwei Zhang
Peng Cui
Wenwu Zhu
GNN
39
1,320
0
11 Dec 2018
Implicit Self-Regularization in Deep Neural Networks: Evidence from
  Random Matrix Theory and Implications for Learning
Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning
Charles H. Martin
Michael W. Mahoney
AI4CE
32
190
0
02 Oct 2018
Entropy and mutual information in models of deep neural networks
Entropy and mutual information in models of deep neural networks
Marylou Gabrié
Andre Manoel
Clément Luneau
Jean Barbier
N. Macris
Florent Krzakala
Lenka Zdeborová
30
178
0
24 May 2018
Measuring and regularizing networks in function space
Measuring and regularizing networks in function space
Ari S. Benjamin
David Rolnick
Konrad Paul Kording
21
137
0
21 May 2018
Change Detection in Graph Streams by Learning Graph Embeddings on
  Constant-Curvature Manifolds
Change Detection in Graph Streams by Learning Graph Embeddings on Constant-Curvature Manifolds
Daniele Grattarola
Daniele Zambon
Cesare Alippi
L. Livi
GNN
35
40
0
16 May 2018
Instance Optimal Decoding and the Restricted Isometry Property
Instance Optimal Decoding and the Restricted Isometry Property
Nicolas Keriven
Rémi Gribonval
21
8
0
27 Feb 2018
Intriguing Properties of Randomly Weighted Networks: Generalizing While
  Learning Next to Nothing
Intriguing Properties of Randomly Weighted Networks: Generalizing While Learning Next to Nothing
Amir Rosenfeld
John K. Tsotsos
MLT
26
51
0
02 Feb 2018
From BoW to CNN: Two Decades of Texture Representation for Texture
  Classification
From BoW to CNN: Two Decades of Texture Representation for Texture Classification
Li Liu
Jie Chen
Paul Fieguth
Guoying Zhao
Rama Chellappa
M. Pietikäinen
3DV
39
332
0
31 Jan 2018
Dropping Activation Outputs with Localized First-layer Deep Network for
  Enhancing User Privacy and Data Security
Dropping Activation Outputs with Localized First-layer Deep Network for Enhancing User Privacy and Data Security
Hao Dong
Chao Wu
Zhen Wei
Yike Guo
38
30
0
20 Nov 2017
Convolutional Neural Networks Analyzed via Convolutional Sparse Coding
Convolutional Neural Networks Analyzed via Convolutional Sparse Coding
V. Papyan
Yaniv Romano
Michael Elad
56
284
0
27 Jul 2016
Sketching for Large-Scale Learning of Mixture Models
Sketching for Large-Scale Learning of Mixture Models
Nicolas Keriven
Anthony Bourrier
Rémi Gribonval
Patrick Pérez
25
75
0
09 Jun 2016
Robust Large Margin Deep Neural Networks
Robust Large Margin Deep Neural Networks
Jure Sokolić
Raja Giryes
Guillermo Sapiro
M. Rodrigues
26
307
0
26 May 2016
On the Stability of Deep Networks
On the Stability of Deep Networks
Raja Giryes
Guillermo Sapiro
A. Bronstein
42
14
0
18 Dec 2014
MatConvNet - Convolutional Neural Networks for MATLAB
MatConvNet - Convolutional Neural Networks for MATLAB
Andrea Vedaldi
Karel Lenc
183
2,946
0
15 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
179
1,185
0
30 Nov 2014
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