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Boosting Semi-Supervised Learning with Contrastive Complementary
  Labeling

Boosting Semi-Supervised Learning with Contrastive Complementary Labeling

13 December 2022
Qinyi Deng
Yong Guo
Zhibang Yang
Haolin Pan
Jian Chen
ArXivPDFHTML

Papers citing "Boosting Semi-Supervised Learning with Contrastive Complementary Labeling"

14 / 14 papers shown
Title
DAdEE: Unsupervised Domain Adaptation in Early Exit PLMs
DAdEE: Unsupervised Domain Adaptation in Early Exit PLMs
Divya J. Bajpai
M. Hanawal
31
0
0
06 Oct 2024
Enhanced Long-Tailed Recognition with Contrastive CutMix Augmentation
Enhanced Long-Tailed Recognition with Contrastive CutMix Augmentation
Haolin Pan
Yong Guo
Mianjie Yu
Jian Chen
49
1
0
06 Jul 2024
Learning with Complementary Labels Revisited: The
  Selected-Completely-at-Random Setting Is More Practical
Learning with Complementary Labels Revisited: The Selected-Completely-at-Random Setting Is More Practical
Wei Wang
Takashi Ishida
Yu-Jie Zhang
Gang Niu
Masashi Sugiyama
27
2
0
27 Nov 2023
Enhancing Label Sharing Efficiency in Complementary-Label Learning with
  Label Augmentation
Enhancing Label Sharing Efficiency in Complementary-Label Learning with Label Augmentation
Weiliang Lin
Gang Niu
Hsuan-Tien Lin
Masashi Sugiyama
6
0
0
15 May 2023
Downscaled Representation Matters: Improving Image Rescaling with
  Collaborative Downscaled Images
Downscaled Representation Matters: Improving Image Rescaling with Collaborative Downscaled Images
Bing Xu
Yong Guo
Luo Jiang
Mianjie Yu
Jian Chen
26
13
0
19 Nov 2022
Automated Dominative Subspace Mining for Efficient Neural Architecture
  Search
Automated Dominative Subspace Mining for Efficient Neural Architecture Search
Yaofo Chen
Yong Guo
Daihai Liao
Fanbing Lv
Hengjie Song
James Tin-Yau Kwok
Mingkui Tan
31
4
0
31 Oct 2022
Improving Robustness by Enhancing Weak Subnets
Improving Robustness by Enhancing Weak Subnets
Yong Guo
David Stutz
Bernt Schiele
AAML
21
15
0
30 Jan 2022
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo
  Labeling
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling
Bowen Zhang
Yidong Wang
Wenxin Hou
Hao Wu
Jindong Wang
Manabu Okumura
T. Shinozaki
AAML
231
862
0
15 Oct 2021
Emerging Properties in Self-Supervised Vision Transformers
Emerging Properties in Self-Supervised Vision Transformers
Mathilde Caron
Hugo Touvron
Ishan Misra
Hervé Jégou
Julien Mairal
Piotr Bojanowski
Armand Joulin
317
5,775
0
29 Apr 2021
Semi-Supervised Semantic Segmentation with Pixel-Level Contrastive
  Learning from a Class-wise Memory Bank
Semi-Supervised Semantic Segmentation with Pixel-Level Contrastive Learning from a Class-wise Memory Bank
Inigo Alonso
Alberto Sabater
David Ferstl
Luis Montesano
Ana C. Murillo
SSL
CLL
124
203
0
27 Apr 2021
SelfMatch: Combining Contrastive Self-Supervision and Consistency for
  Semi-Supervised Learning
SelfMatch: Combining Contrastive Self-Supervision and Consistency for Semi-Supervised Learning
Byoungjip Kim
Jinho Choo
Yeong-Dae Kwon
Seongho Joe
Seungjai Min
Youngjune Gwon
SSL
27
52
0
16 Jan 2021
Meta Pseudo Labels
Meta Pseudo Labels
Hieu H. Pham
Zihang Dai
Qizhe Xie
Minh-Thang Luong
Quoc V. Le
VLM
253
656
0
23 Mar 2020
Hierarchical Neural Architecture Search for Single Image
  Super-Resolution
Hierarchical Neural Architecture Search for Single Image Super-Resolution
Yong Guo
Yongsheng Luo
Zhenhao He
Jin Huang
Jian Chen
SupR
59
49
0
10 Mar 2020
There Are Many Consistent Explanations of Unlabeled Data: Why You Should
  Average
There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average
Ben Athiwaratkun
Marc Finzi
Pavel Izmailov
A. Wilson
199
243
0
14 Jun 2018
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