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LayerMatch: Do Pseudo-labels Benefit All Layers?

LayerMatch: Do Pseudo-labels Benefit All Layers?

20 June 2024
Chaoqi Liang
Guanglei Yang
Lifeng Qiao
Zitong Huang
Hongliang Yan
Yunchao Wei
W. Zuo
ArXivPDFHTML

Papers citing "LayerMatch: Do Pseudo-labels Benefit All Layers?"

4 / 4 papers shown
Title
Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few
  Labels
Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels
Zebin You
Yong Zhong
Fan Bao
Jiacheng Sun
Chongxuan Li
Jun Zhu
DiffM
VLM
187
35
0
21 Feb 2023
Dataset Pruning: Reducing Training Data by Examining Generalization
  Influence
Dataset Pruning: Reducing Training Data by Examining Generalization Influence
Shuo Yang
Zeke Xie
Hanyu Peng
Minjing Xu
Mingming Sun
P. Li
DD
132
106
0
19 May 2022
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
170
251
0
15 May 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
201
848
0
15 Oct 2021
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