Generating Unbiased Pseudo-labels via a Theoretically Guaranteed Chebyshev Constraint to Unify Semi-supervised Classification and Regression

3 November 2023

Papers citing "Generating Unbiased Pseudo-labels via a Theoretically Guaranteed Chebyshev Constraint to Unify Semi-supervised Classification and Regression"

6 / 6 papers shown

Title
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 160 3,572 0 21 Jan 2020
Self-training with Noisy Student improves ImageNet classification Qizhe Xie Minh-Thang Luong Eduard H. Hovy Quoc V. Le NoLa 315 2,392 0 11 Nov 2019
RandAugment: Practical automated data augmentation with a reduced search space E. D. Cubuk Barret Zoph Jonathon Shlens Quoc V. Le MQ 250 3,502 0 30 Sep 2019
Deep High-Resolution Representation Learning for Human Pose Estimation Ke Sun Bin Xiao Dong Liu Jingdong Wang 3DV 136 4,062 0 25 Feb 2019
Temporal Ensembling for Semi-Supervised Learning S. Laine Timo Aila UQCV 185 2,567 0 07 Oct 2016
Stacked Hourglass Networks for Human Pose Estimation Alejandro Newell Kaiyu Yang Jia Deng 3DH 119 5,037 0 22 Mar 2016