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SequenceMatch: Revisiting the design of weak-strong augmentations for
  Semi-supervised learning

SequenceMatch: Revisiting the design of weak-strong augmentations for Semi-supervised learning

24 October 2023
Khanh-Binh Nguyen
ArXiv (abs)PDFHTMLGithub (4★)

Papers citing "SequenceMatch: Revisiting the design of weak-strong augmentations for Semi-supervised learning"

26 / 26 papers shown
Title
FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning
FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning
Yidong Wang
Hao Chen
Qiang Heng
Wenxin Hou
Yue Fan
...
Marios Savvides
T. Shinozaki
Bhiksha Raj
Bernt Schiele
Xing Xie
221
278
0
15 May 2022
SimMatch: Semi-supervised Learning with Similarity Matching
SimMatch: Semi-supervised Learning with Similarity Matching
Mingkai Zheng
Shan You
Lang Huang
Fei Wang
Chao Qian
Chang Xu
92
183
0
14 Mar 2022
Regularising for invariance to data augmentation improves supervised
  learning
Regularising for invariance to data augmentation improves supervised learning
Aleksander Botev
Matthias Bauer
Soham De
81
14
0
07 Mar 2022
ABC: Auxiliary Balanced Classifier for Class-imbalanced Semi-supervised
  Learning
ABC: Auxiliary Balanced Classifier for Class-imbalanced Semi-supervised Learning
Hyuck Lee
Seungjae Shin
Heeyoung Kim
CLL
63
94
0
20 Oct 2021
Dash: Semi-Supervised Learning with Dynamic Thresholding
Dash: Semi-Supervised Learning with Dynamic Thresholding
Yi Tian Xu
Lei Shang
Jinxing Ye
Qi Qian
Yu-Feng Li
Baigui Sun
Hao Li
Rong Jin
113
225
0
01 Sep 2021
Semi-Supervised Learning with Multi-Head Co-Training
Semi-Supervised Learning with Multi-Head Co-Training
Mingcai Chen
Yuntao Du
Yi Zhang
Shuwei Qian
Chong-Jun Wang
70
30
0
10 Jul 2021
CReST: A Class-Rebalancing Self-Training Framework for Imbalanced
  Semi-Supervised Learning
CReST: A Class-Rebalancing Self-Training Framework for Imbalanced Semi-Supervised Learning
Chen Wei
Kihyuk Sohn
Clayton Mellina
Alan Yuille
Fan Yang
CLL
107
265
0
18 Feb 2021
Exponential Moving Average Normalization for Self-supervised and
  Semi-supervised Learning
Exponential Moving Average Normalization for Self-supervised and Semi-supervised Learning
Zhaowei Cai
Avinash Ravichandran
Subhransu Maji
Charless C. Fowlkes
Zhuowen Tu
Stefano Soatto
107
120
0
21 Jan 2021
CoMatch: Semi-supervised Learning with Contrastive Graph Regularization
CoMatch: Semi-supervised Learning with Contrastive Graph Regularization
Junnan Li
Caiming Xiong
Guosheng Lin
SSL
84
263
0
23 Nov 2020
Balanced Meta-Softmax for Long-Tailed Visual Recognition
Balanced Meta-Softmax for Long-Tailed Visual Recognition
Jiawei Ren
Cunjun Yu
Shunan Sheng
Xiao Ma
Haiyu Zhao
Shuai Yi
Hongsheng Li
204
572
0
21 Jul 2020
Meta Pseudo Labels
Meta Pseudo Labels
Hieu H. Pham
Zihang Dai
Qizhe Xie
Minh-Thang Luong
Quoc V. Le
VLM
345
671
0
23 Mar 2020
Improved Baselines with Momentum Contrastive Learning
Improved Baselines with Momentum Contrastive Learning
Xinlei Chen
Haoqi Fan
Ross B. Girshick
Kaiming He
SSL
503
3,444
0
09 Mar 2020
A Simple Framework for Contrastive Learning of Visual Representations
A Simple Framework for Contrastive Learning of Visual Representations
Ting-Li Chen
Simon Kornblith
Mohammad Norouzi
Geoffrey E. Hinton
SSL
390
18,897
0
13 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
163
3,578
0
21 Jan 2020
Momentum Contrast for Unsupervised Visual Representation Learning
Momentum Contrast for Unsupervised Visual Representation Learning
Kaiming He
Haoqi Fan
Yuxin Wu
Saining Xie
Ross B. Girshick
SSL
216
12,136
0
13 Nov 2019
Self-training with Noisy Student improves ImageNet classification
Self-training with Noisy Student improves ImageNet classification
Qizhe Xie
Minh-Thang Luong
Eduard H. Hovy
Quoc V. Le
NoLa
315
2,393
0
11 Nov 2019
Exploring the Limits of Transfer Learning with a Unified Text-to-Text
  Transformer
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Colin Raffel
Noam M. Shazeer
Adam Roberts
Katherine Lee
Sharan Narang
Michael Matena
Yanqi Zhou
Wei Li
Peter J. Liu
AIMat
490
20,342
0
23 Oct 2019
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
260
3,505
0
30 Sep 2019
Unsupervised Data Augmentation for Consistency Training
Unsupervised Data Augmentation for Consistency Training
Qizhe Xie
Zihang Dai
Eduard H. Hovy
Minh-Thang Luong
Quoc V. Le
137
2,323
0
29 Apr 2019
Exploring the Limits of Weakly Supervised Pretraining
Exploring the Limits of Weakly Supervised Pretraining
D. Mahajan
Ross B. Girshick
Vignesh Ramanathan
Kaiming He
Manohar Paluri
Yixuan Li
Ashwin R. Bharambe
Laurens van der Maaten
VLM
205
1,370
0
02 May 2018
Improved Regularization of Convolutional Neural Networks with Cutout
Improved Regularization of Convolutional Neural Networks with Cutout
Terrance Devries
Graham W. Taylor
137
3,775
0
15 Aug 2017
Virtual Adversarial Training: A Regularization Method for Supervised and
  Semi-Supervised Learning
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning
Takeru Miyato
S. Maeda
Masanori Koyama
S. Ishii
GAN
153
2,739
0
13 Apr 2017
Temporal Ensembling for Semi-Supervised Learning
Temporal Ensembling for Semi-Supervised Learning
S. Laine
Timo Aila
UQCV
189
2,567
0
07 Oct 2016
SGDR: Stochastic Gradient Descent with Warm Restarts
SGDR: Stochastic Gradient Descent with Warm Restarts
I. Loshchilov
Frank Hutter
ODL
350
8,179
0
13 Aug 2016
Wide Residual Networks
Wide Residual Networks
Sergey Zagoruyko
N. Komodakis
356
8,002
0
23 May 2016
Semi-Supervised Learning with Ladder Networks
Semi-Supervised Learning with Ladder Networks
Antti Rasmus
Harri Valpola
Mikko Honkala
Mathias Berglund
T. Raiko
SSL
102
1,372
0
09 Jul 2015
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