Learning Label Refinement and Threshold Adjustment for Imbalanced
Semi-Supervised Learning

Learning Label Refinement and Threshold Adjustment for Imbalanced Semi-Supervised Learning

7 July 2024

Chen Chen

Papers citing "Learning Label Refinement and Threshold Adjustment for Imbalanced Semi-Supervised Learning"

5 / 5 papers shown

Title
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 175 251 0 15 May 2022
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling Bowen Zhang Yidong Wang Wenxin Hou Hao Wu Jindong Wang Manabu Okumura T. Shinozaki AAML 213 848 0 15 Oct 2021
In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning Mamshad Nayeem Rizve Kevin Duarte Y. S. Rawat M. Shah 203 501 0 15 Jan 2021
Neural Architecture Search with Reinforcement Learning Barret Zoph Quoc V. Le 264 5,290 0 05 Nov 2016
SMOTE: Synthetic Minority Over-sampling Technique Nitesh V. Chawla Kevin W. Bowyer Lawrence Hall W. Kegelmeyer AI4TS 160 25,150 0 09 Jun 2011