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Discovery and Separation of Features for Invariant Representation
  Learning

Discovery and Separation of Features for Invariant Representation Learning

2 December 2019
Ayush Jaiswal
Rob Brekelmans
Daniel Moyer
Greg Ver Steeg
Wael AbdAlmageed
Premkumar Natarajan
    CMLOOD
ArXiv (abs)PDFHTML

Papers citing "Discovery and Separation of Features for Invariant Representation Learning"

8 / 8 papers shown
Title
Invariant Representations through Adversarial Forgetting
Invariant Representations through Adversarial Forgetting
Ayush Jaiswal
Daniel Moyer
Greg Ver Steeg
Wael AbdAlmageed
Premkumar Natarajan
OOD
46
38
0
11 Nov 2019
RoPAD: Robust Presentation Attack Detection through Unsupervised
  Adversarial Invariance
RoPAD: Robust Presentation Attack Detection through Unsupervised Adversarial Invariance
Ayush Jaiswal
Shuai Xia
I. Masi
Wael AbdAlmageed
AAML
54
15
0
08 Mar 2019
Invariant Representations without Adversarial Training
Invariant Representations without Adversarial Training
Daniel Moyer
Shuyang Gao
Rob Brekelmans
Greg Ver Steeg
Aram Galstyan
OOD
64
210
0
24 May 2018
Dynamic Routing Between Capsules
Dynamic Routing Between Capsules
S. Sabour
Nicholas Frosst
Geoffrey E. Hinton
177
4,596
0
26 Oct 2017
Controllable Invariance through Adversarial Feature Learning
Controllable Invariance through Adversarial Feature Learning
Qizhe Xie
Zihang Dai
Yulun Du
Eduard H. Hovy
Graham Neubig
OOD
94
292
0
31 May 2017
Survey on Feature Selection
Survey on Feature Selection
T. Abdallah
B. Iglesia
110
232
0
10 Oct 2015
Domain-Adversarial Training of Neural Networks
Domain-Adversarial Training of Neural Networks
Yaroslav Ganin
E. Ustinova
Hana Ajakan
Pascal Germain
Hugo Larochelle
François Laviolette
M. Marchand
Victor Lempitsky
GANOOD
378
9,497
0
28 May 2015
A Kernel Method for the Two-Sample Problem
A Kernel Method for the Two-Sample Problem
Arthur Gretton
Karsten Borgwardt
Malte J. Rasch
Bernhard Schölkopf
Alex Smola
231
2,363
0
15 May 2008
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