Don't fear the unlabelled: safe semi-supervised learning via simple debiasing

14 March 2022

Papers citing "Don't fear the unlabelled: safe semi-supervised learning via simple debiasing"

10 / 10 papers shown

Title
Theory-inspired Label Shift Adaptation via Aligned Distribution Mixture Ruidong Fan Xiao Ouyang Hong Tao Yuhua Qian Chenping Hou OOD 49 0 0 04 Nov 2024
Towards Understanding Why FixMatch Generalizes Better Than Supervised Learning Jingyang Li Jiachun Pan Vincent Y. F. Tan Kim-Chuan Toh Pan Zhou AAML MLT 48 0 0 15 Oct 2024
Enhancing Semi-Supervised Learning via Representative and Diverse Sample Selection Qian Shao Jiangrui Kang Qiyuan Chen Zepeng Li Hongxia Xu Yiwen Cao Jiajuan Liang Jian Wu 28 0 0 18 Sep 2024
Prediction De-Correlated Inference: A safe approach for post-prediction inference Feng Gan Wanfeng Liang Changliang Zou 21 0 0 11 Dec 2023
On Non-Random Missing Labels in Semi-Supervised Learning Xinting Hu Yulei Niu C. Miao Xiansheng Hua Hanwang Zhang 34 18 0 29 Jun 2022
MedMNIST v2 -- A large-scale lightweight benchmark for 2D and 3D biomedical image classification Jiancheng Yang Rui Shi D. Wei Zequan Liu Lin Zhao B. Ke Hanspeter Pfister Bingbing Ni VLM 185 648 0 27 Oct 2021
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling Bowen Zhang Yidong Wang Wenxin Hou Hao Wu Jindong Wang Manabu Okumura T. Shinozaki AAML 255 862 0 15 Oct 2021
The Rich Get Richer: Disparate Impact of Semi-Supervised Learning Zhaowei Zhu Tianyi Luo Yang Liu 150 39 0 12 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 241 509 0 15 Jan 2021
Meta Pseudo Labels Hieu H. Pham Zihang Dai Qizhe Xie Minh-Thang Luong Quoc V. Le VLM 262 656 0 23 Mar 2020