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Learning Invariant Representation with Consistency and Diversity for
  Semi-supervised Source Hypothesis Transfer
v1v2 (latest)

Learning Invariant Representation with Consistency and Diversity for Semi-supervised Source Hypothesis Transfer

7 July 2021
Xiaodong Wang
Junbao Zhuo
Shuhao Cui
Shuhui Wang
ArXiv (abs)PDFHTMLGithub (17★)

Papers citing "Learning Invariant Representation with Consistency and Diversity for Semi-supervised Source Hypothesis Transfer"

39 / 39 papers shown
Title
Model Adaptation: Unsupervised Domain Adaptation without Source Data
Model Adaptation: Unsupervised Domain Adaptation without Source Data
Rui Li
Qianfen Jiao
Wenming Cao
Hau-San Wong
Si Wu
OOD
261
492
0
26 Feb 2025
Source Data-absent Unsupervised Domain Adaptation through Hypothesis
  Transfer and Labeling Transfer
Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer
Jian Liang
Dapeng Hu
Yunbo Wang
Ran He
Jiashi Feng
189
257
0
14 Dec 2020
Selective Pseudo-Labeling with Reinforcement Learning for
  Semi-Supervised Domain Adaptation
Selective Pseudo-Labeling with Reinforcement Learning for Semi-Supervised Domain Adaptation
Bingyu Liu
Yuhong Guo
Jieping Ye
Weihong Deng
57
3
0
07 Dec 2020
Effective Label Propagation for Discriminative Semi-Supervised Domain
  Adaptation
Effective Label Propagation for Discriminative Semi-Supervised Domain Adaptation
Zhiyong Huang
Kekai Sheng
Weiming Dong
Xing Mei
Chongyang Ma
Feiyue Huang
D. Zhou
Changsheng Xu
115
7
0
04 Dec 2020
Heuristic Domain Adaptation
Heuristic Domain Adaptation
Shuhao Cui
Xuan Jin
Shuhui Wang
Yuan He
Qingming Huang
107
49
0
30 Nov 2020
Learning Invariant Representations and Risks for Semi-supervised Domain
  Adaptation
Learning Invariant Representations and Risks for Semi-supervised Domain Adaptation
Yue Liu
Yezhen Wang
Shanghang Zhang
Dongsheng Li
Trevor Darrell
Kurt Keutzer
Han Zhao
OOD
59
96
0
09 Oct 2020
Attract, Perturb, and Explore: Learning a Feature Alignment Network for
  Semi-supervised Domain Adaptation
Attract, Perturb, and Explore: Learning a Feature Alignment Network for Semi-supervised Domain Adaptation
Taekyung Kim
Changick Kim
82
139
0
18 Jul 2020
Online Meta-Learning for Multi-Source and Semi-Supervised Domain
  Adaptation
Online Meta-Learning for Multi-Source and Semi-Supervised Domain Adaptation
Da Li
Timothy M. Hospedales
72
103
0
09 Apr 2020
Universal Source-Free Domain Adaptation
Universal Source-Free Domain Adaptation
Jogendra Nath Kundu
Naveen Venkat
V. RahulM.
R. Venkatesh Babu
VLMTTA
77
343
0
09 Apr 2020
Gradually Vanishing Bridge for Adversarial Domain Adaptation
Gradually Vanishing Bridge for Adversarial Domain Adaptation
Shuhao Cui
Shuhui Wang
Junbao Zhuo
Chi Su
Qingming Huang
Q. Tian
123
246
0
30 Mar 2020
Towards Discriminability and Diversity: Batch Nuclear-norm Maximization
  under Label Insufficient Situations
Towards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Situations
Shuhao Cui
Shuhui Wang
Junbao Zhuo
Liang Li
Qingming Huang
Q. Tian
81
367
0
27 Mar 2020
Domain Adaptation with Conditional Distribution Matching and Generalized
  Label Shift
Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift
Rémi Tachet des Combes
Han Zhao
Yu Wang
Geoffrey J. Gordon
OODAAMLVLM
76
189
0
10 Mar 2020
Do We Really Need to Access the Source Data? Source Hypothesis Transfer
  for Unsupervised Domain Adaptation
Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation
Jian Liang
Dapeng Hu
Jiashi Feng
113
1,248
0
20 Feb 2020
FixMatch: Simplifying Semi-Supervised Learning with Consistency and
  Confidence
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
Kihyuk Sohn
David Berthelot
Chun-Liang Li
Zizhao Zhang
Nicholas Carlini
E. D. Cubuk
Alexey Kurakin
Han Zhang
Colin Raffel
AAML
160
3,572
0
21 Jan 2020
RandAugment: Practical automated data augmentation with a reduced search
  space
RandAugment: Practical automated data augmentation with a reduced search space
E. D. Cubuk
Barret Zoph
Jonathon Shlens
Quoc V. Le
MQ
244
3,503
0
30 Sep 2019
$d$-SNE: Domain Adaptation using Stochastic Neighborhood Embedding
ddd-SNE: Domain Adaptation using Stochastic Neighborhood Embedding
Xiang Xu
Xiong Zhou
Ragav Venkatesan
Gurumurthy Swaminathan
Orchid Majumder
60
120
0
29 May 2019
MixMatch: A Holistic Approach to Semi-Supervised Learning
MixMatch: A Holistic Approach to Semi-Supervised Learning
David Berthelot
Nicholas Carlini
Ian Goodfellow
Nicolas Papernot
Avital Oliver
Colin Raffel
151
3,033
0
06 May 2019
Semi-supervised Domain Adaptation via Minimax Entropy
Semi-supervised Domain Adaptation via Minimax Entropy
Kuniaki Saito
Donghyun Kim
Stan Sclaroff
Trevor Darrell
Kate Saenko
75
622
0
13 Apr 2019
Bridging Theory and Algorithm for Domain Adaptation
Bridging Theory and Algorithm for Domain Adaptation
Yuchen Zhang
Tianle Liu
Mingsheng Long
Michael I. Jordan
83
713
0
11 Apr 2019
Interpolation Consistency Training for Semi-Supervised Learning
Interpolation Consistency Training for Semi-Supervised Learning
Vikas Verma
Kenji Kawaguchi
Alex Lamb
Arno Solin
Arno Solin
Yoshua Bengio
David Lopez-Paz
110
770
0
09 Mar 2019
Domain Adaptation with Asymmetrically-Relaxed Distribution Alignment
Domain Adaptation with Asymmetrically-Relaxed Distribution Alignment
Yifan Wu
Ezra Winston
Divyansh Kaushik
Zachary Chase Lipton
58
127
0
05 Mar 2019
Moment Matching for Multi-Source Domain Adaptation
Moment Matching for Multi-Source Domain Adaptation
Xingchao Peng
Qinxun Bai
Xide Xia
Zijun Huang
Kate Saenko
Bo Wang
OOD
143
1,809
0
04 Dec 2018
CyCADA: Cycle-Consistent Adversarial Domain Adaptation
CyCADA: Cycle-Consistent Adversarial Domain Adaptation
Judy Hoffman
Eric Tzeng
Taesung Park
Jun-Yan Zhu
Phillip Isola
Kate Saenko
Alexei A. Efros
Trevor Darrell
147
3,002
0
08 Nov 2017
Adversarial Dropout Regularization
Adversarial Dropout Regularization
Kuniaki Saito
Yoshitaka Ushiku
Tatsuya Harada
Kate Saenko
GAN
72
286
0
05 Nov 2017
mixup: Beyond Empirical Risk Minimization
mixup: Beyond Empirical Risk Minimization
Hongyi Zhang
Moustapha Cissé
Yann N. Dauphin
David Lopez-Paz
NoLa
282
9,797
0
25 Oct 2017
VisDA: The Visual Domain Adaptation Challenge
VisDA: The Visual Domain Adaptation Challenge
Xingchao Peng
Ben Usman
Neela Kaushik
Judy Hoffman
Dequan Wang
Kate Saenko
OOD
91
806
0
18 Oct 2017
Deep Hashing Network for Unsupervised Domain Adaptation
Deep Hashing Network for Unsupervised Domain Adaptation
Hemanth Venkateswara
José Eusébio
Shayok Chakraborty
S. Panchanathan
OOD
147
2,057
0
22 Jun 2017
Mind the Class Weight Bias: Weighted Maximum Mean Discrepancy for
  Unsupervised Domain Adaptation
Mind the Class Weight Bias: Weighted Maximum Mean Discrepancy for Unsupervised Domain Adaptation
Hongliang Yan
Yukang Ding
P. Li
Qilong Wang
Yong-mei Xu
W. Zuo
91
576
0
01 May 2017
Central Moment Discrepancy (CMD) for Domain-Invariant Representation
  Learning
Central Moment Discrepancy (CMD) for Domain-Invariant Representation Learning
Werner Zellinger
Thomas Grubinger
E. Lughofer
T. Natschläger
Susanne Saminger-Platz
OOD
105
577
0
28 Feb 2017
Temporal Ensembling for Semi-Supervised Learning
Temporal Ensembling for Semi-Supervised Learning
S. Laine
Timo Aila
UQCV
185
2,566
0
07 Oct 2016
Deep CORAL: Correlation Alignment for Deep Domain Adaptation
Deep CORAL: Correlation Alignment for Deep Domain Adaptation
Baochen Sun
Kate Saenko
OOD
105
3,161
0
06 Jul 2016
Coupled Generative Adversarial Networks
Coupled Generative Adversarial Networks
Ming-Yuan Liu
Oncel Tuzel
OODGAN
98
1,625
0
24 Jun 2016
Regularization With Stochastic Transformations and Perturbations for
  Deep Semi-Supervised Learning
Regularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning
Mehdi S. M. Sajjadi
Mehran Javanmardi
Tolga Tasdizen
BDL
85
1,115
0
14 Jun 2016
Deep Transfer Learning with Joint Adaptation Networks
Deep Transfer Learning with Joint Adaptation Networks
Mingsheng Long
Hanhua Zhu
Jianmin Wang
Michael I. Jordan
TTA
96
2,459
0
21 May 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,322
0
10 Dec 2015
Learning Transferable Features with Deep Adaptation Networks
Learning Transferable Features with Deep Adaptation Networks
Mingsheng Long
Yue Cao
Jianmin Wang
Michael I. Jordan
OOD
220
5,211
0
10 Feb 2015
Deep Domain Confusion: Maximizing for Domain Invariance
Deep Domain Confusion: Maximizing for Domain Invariance
Eric Tzeng
Judy Hoffman
Ning Zhang
Kate Saenko
Trevor Darrell
OOD
172
2,605
0
10 Dec 2014
Unsupervised Domain Adaptation by Backpropagation
Unsupervised Domain Adaptation by Backpropagation
Yaroslav Ganin
Victor Lempitsky
OOD
235
6,041
0
26 Sep 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAttMDE
1.7K
100,479
0
04 Sep 2014
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