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A Theory-Driven Self-Labeling Refinement Method for Contrastive
  Representation Learning

A Theory-Driven Self-Labeling Refinement Method for Contrastive Representation Learning

28 June 2021
Pan Zhou
Caiming Xiong
Xiaotong Yuan
S. Hoi
    SSL
ArXivPDFHTML

Papers citing "A Theory-Driven Self-Labeling Refinement Method for Contrastive Representation Learning"

6 / 6 papers shown
Title
Self-Labeling Refinement for Robust Representation Learning with
  Bootstrap Your Own Latent
Self-Labeling Refinement for Robust Representation Learning with Bootstrap Your Own Latent
Siddhant Garg
Dhruval Jain
SSL
42
0
0
09 Apr 2022
On the Importance of Asymmetry for Siamese Representation Learning
On the Importance of Asymmetry for Siamese Representation Learning
Tianlin Li
Haoqi Fan
Yuandong Tian
Daisuke Kihara
Xinlei Chen
SSL
27
51
0
01 Apr 2022
Prototypical Graph Contrastive Learning
Prototypical Graph Contrastive Learning
Shuai Lin
Pan Zhou
Zi-Yuan Hu
Shuojia Wang
Ruihui Zhao
Yefeng Zheng
Liang Lin
Eric P. Xing
Xiaodan Liang
21
86
0
17 Jun 2021
MixCo: Mix-up Contrastive Learning for Visual Representation
MixCo: Mix-up Contrastive Learning for Visual Representation
Sungnyun Kim
Gihun Lee
Sangmin Bae
Seyoung Yun
SSL
109
80
0
13 Oct 2020
Improved Baselines with Momentum Contrastive Learning
Improved Baselines with Momentum Contrastive Learning
Xinlei Chen
Haoqi Fan
Ross B. Girshick
Kaiming He
SSL
267
3,371
0
09 Mar 2020
Benefits of depth in neural networks
Benefits of depth in neural networks
Matus Telgarsky
142
602
0
14 Feb 2016
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