Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning

8 August 2019

Papers citing "Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning"

5 / 205 papers shown

Title
Near real-time map building with multi-class image set labelling and classification of road conditions using convolutional neural networks S. Ramanna Cenker Sengoz S. Kehler D. Pham 24 12 0 27 Jan 2020
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 104 3,495 0 21 Jan 2020
Self-training with Noisy Student improves ImageNet classification Qizhe Xie Minh-Thang Luong Eduard H. Hovy Quoc V. Le NoLa 88 2,370 0 11 Nov 2019
Energy Models for Better Pseudo-Labels: Improving Semi-Supervised Classification with the 1-Laplacian Graph Energy Angelica I. Aviles-Rivero Nicolas Papadakis Ruoteng Li P. Sellars Samar M. Alsaleh R. Tan Carola-Bibiane Schönlieb 37 3 0 20 Jun 2019
There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average Ben Athiwaratkun Marc Finzi Pavel Izmailov A. Wilson 229 243 0 14 Jun 2018