MixMatch: A Holistic Approach to Semi-Supervised Learning

6 May 2019

Papers citing "MixMatch: A Holistic Approach to Semi-Supervised Learning"

20 / 570 papers shown

Title
Parting with Illusions about Deep Active Learning Sudhanshu Mittal Maxim Tatarchenko Özgün Çiçek Thomas Brox VLM 21 59 0 11 Dec 2019
The Group Loss for Deep Metric Learning Ismail Elezi Sebastiano Vascon Alessandro Torcinovich Marcello Pelillo Laura Leal-Taixe 14 50 0 01 Dec 2019
Rethinking deep active learning: Using unlabeled data at model training Oriane Siméoni Mateusz Budnik Yannis Avrithis G. Gravier HAI 27 79 0 19 Nov 2019
Self-training with Noisy Student improves ImageNet classification Qizhe Xie Minh-Thang Luong Eduard H. Hovy Quoc V. Le NoLa 55 2,362 0 11 Nov 2019
Modeling EEG data distribution with a Wasserstein Generative Adversarial Network to predict RSVP Events Sharaj Panwar P. Rad T. Jung Yufei Huang GAN 31 50 0 11 Nov 2019
Weakly Supervised Deep Learning Approach in Streaming Environments Mahardhika Pratama Andri Ashfahani Mohamad Abdul Hady 11 13 0 03 Nov 2019
Learning from Label Proportions with Consistency Regularization Kuen-Han Tsai Hsuan-Tien Lin 19 44 0 29 Oct 2019
Consistency Regularization for Generative Adversarial Networks Han Zhang Zizhao Zhang Augustus Odena Honglak Lee GAN 22 284 0 26 Oct 2019
GraphMix: Improved Training of GNNs for Semi-Supervised Learning Vikas Verma Meng Qu Kenji Kawaguchi Alex Lamb Yoshua Bengio Arno Solin Jian Tang 33 62 0 25 Sep 2019
Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks Tianyu Pang Kun Xu Jun Zhu AAML 28 103 0 25 Sep 2019
And the Bit Goes Down: Revisiting the Quantization of Neural Networks Pierre Stock Armand Joulin Rémi Gribonval Benjamin Graham Hervé Jégou MQ 34 149 0 12 Jul 2019
Asymptotic Bayes risk for Gaussian mixture in a semi-supervised setting Marc Lelarge Léo Miolane 14 28 0 08 Jul 2019
Semi-supervised semantic segmentation needs strong, varied perturbations Geoff French S. Laine Timo Aila Michal Mackiewicz G. Finlayson 29 29 0 05 Jun 2019
Learning Representations by Maximizing Mutual Information Across Views Philip Bachman R. Devon Hjelm William Buchwalter SSL 72 1,455 0 03 Jun 2019
Achieving Generalizable Robustness of Deep Neural Networks by Stability Training Jan Laermann Wojciech Samek Nils Strodthoff OOD 24 15 0 03 Jun 2019
Semi-Supervised Learning with Scarce Annotations Sylvestre-Alvise Rebuffi Sébastien Ehrhardt Kai Han Andrea Vedaldi Andrew Zisserman SSL 24 49 0 21 May 2019
Virtual Mixup Training for Unsupervised Domain Adaptation Xudong Mao Yun Ma Zhenguo Yang Yangbin Chen Qing Li 35 52 0 10 May 2019
Interpolation Consistency Training for Semi-Supervised Learning Vikas Verma Kenji Kawaguchi Alex Lamb Arno Solin Arno Solin Yoshua Bengio David Lopez-Paz 39 756 0 09 Mar 2019
There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average Ben Athiwaratkun Marc Finzi Pavel Izmailov A. Wilson 202 243 0 14 Jun 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,675 0 05 Dec 2016