MixMatch: A Holistic Approach to Semi-Supervised Learning

6 May 2019

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

41 / 641 papers shown

Title
Do CNNs Encode Data Augmentations? Eddie Q. Yan Yanping Huang OOD 20 5 0 29 Feb 2020
A U-Net Based Discriminator for Generative Adversarial Networks Edgar Schönfeld Bernt Schiele Anna Khoreva GAN 32 292 0 28 Feb 2020
Semi-Supervised Neural Architecture Search Renqian Luo Xu Tan Rui Wang Tao Qin Enhong Chen Tie-Yan Liu 13 88 0 24 Feb 2020
It's Not What Machines Can Learn, It's What We Cannot Teach Gal Yehuda Moshe Gabel Assaf Schuster FaML 19 37 0 21 Feb 2020
A Simple Framework for Contrastive Learning of Visual Representations Ting-Li Chen Simon Kornblith Mohammad Norouzi Geoffrey E. Hinton SSL 78 18,362 0 13 Feb 2020
Improved Consistency Regularization for GANs Zhengli Zhao Sameer Singh Honglak Lee Zizhao Zhang Augustus Odena Han Zhang 32 153 0 11 Feb 2020
Semi-Supervised Class Discovery Jeremy Nixon J. Liu David Berthelot 20 2 0 10 Feb 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 3,479 0 21 Jan 2020
Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised Learning Paola Cascante-Bonilla Fuwen Tan Yanjun Qi Vicente Ordonez ODL 50 23 0 16 Jan 2020
Improving Image Autoencoder Embeddings with Perceptual Loss G. Pihlgren Fredrik Sandin Marcus Liwicki 25 33 0 10 Jan 2020
Semi-Supervised Learning with Normalizing Flows Pavel Izmailov Polina Kirichenko Marc Finzi A. Wilson DRL BDL 40 111 0 30 Dec 2019
AutoDiscern: Rating the Quality of Online Health Information with Hierarchical Encoder Attention-based Neural Networks Laura Kinkead Ahmed Allam Michael Krauthammer 25 19 0 30 Dec 2019
Discriminative Clustering with Representation Learning with any Ratio of Labeled to Unlabeled Data Corinne Jones Vincent Roulet Zaïd Harchaoui 40 1 0 30 Dec 2019
Learning to Impute: A General Framework for Semi-supervised Learning Wei-Hong Li Chuan-Sheng Foo Hakan Bilen SSL 24 9 0 22 Dec 2019
Triple Generative Adversarial Networks Chongxuan Li Kun Xu Jiashuo Liu Jun Zhu Bo Zhang GAN 36 41 0 20 Dec 2019
RealMix: Towards Realistic Semi-Supervised Deep Learning Algorithms Varun Nair Javier Fuentes Alonso Tony Beltramelli 33 26 0 18 Dec 2019
Parting with Illusions about Deep Active Learning Sudhanshu Mittal Maxim Tatarchenko Özgün Çiçek Thomas Brox VLM 27 59 0 11 Dec 2019
The Group Loss for Deep Metric Learning Ismail Elezi Sebastiano Vascon Alessandro Torcinovich Marcello Pelillo Laura Leal-Taixe 22 50 0 01 Dec 2019
Reinventing 2D Convolutions for 3D Images Jiancheng Yang Xiaoyang Huang Yi He Jingwei Xu Canqian Yang Guozheng Xu Bingbing Ni 24 11 0 24 Nov 2019
Rethinking deep active learning: Using unlabeled data at model training Oriane Siméoni Mateusz Budnik Yannis Avrithis G. Gravier HAI 30 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 88 2,365 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 37 51 0 11 Nov 2019
Weakly Supervised Deep Learning Approach in Streaming Environments Mahardhika Pratama Andri Ashfahani Mohamad Abdul Hady 22 13 0 03 Nov 2019
Learning from Label Proportions with Consistency Regularization Kuen-Han Tsai Hsuan-Tien Lin 27 44 0 29 Oct 2019
Consistency Regularization for Generative Adversarial Networks Han Zhang Zizhao Zhang Augustus Odena Honglak Lee GAN 36 284 0 26 Oct 2019
Consistency-based Semi-supervised Active Learning: Towards Minimizing Labeling Cost M. Gao Zizhao Zhang Guo-Ding Yu Sercan Ö. Arik L. Davis Tomas Pfister 168 196 0 16 Oct 2019
MixMatch Domain Adaptaion: Prize-winning solution for both tracks of VisDA 2019 challenge D. Rukhovich Danil Galeev TTA 24 13 0 09 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
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Zhijun Mai Guosheng Hu Dexiong Chen Fumin Shen Heng Tao Shen 22 41 0 27 Aug 2019
And the Bit Goes Down: Revisiting the Quantization of Neural Networks Pierre Stock Armand Joulin Rémi Gribonval Benjamin Graham Hervé Jégou MQ 37 149 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 36 29 0 05 Jun 2019
Learning Representations by Maximizing Mutual Information Across Views Philip Bachman R. Devon Hjelm William Buchwalter SSL 105 1,459 0 03 Jun 2019
Achieving Generalizable Robustness of Deep Neural Networks by Stability Training Jan Laermann Wojciech Samek Nils Strodthoff OOD 32 15 0 03 Jun 2019
Probabilistic Decoupling of Labels in Classification Jeppe Nørregaard Lars Kai Hansen BDL 22 0 0 29 May 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 38 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 39 757 0 09 Mar 2019
There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average Ben Athiwaratkun Marc Finzi Pavel Izmailov A. Wilson 208 243 0 14 Jun 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,695 0 05 Dec 2016