Algorithms · Semi-Supervised Learning

TitleAuthors
A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised LearningXuanqing Liu · Si Si · Jerry Zhu · Yang Li · Cho-Jui Hsieh
Are Anchor Points Really Indispensable in Label-Noise Learning?Xiaobo Xia · Tongliang Liu · Nannan Wang · Bo Han · Chen Gong · Gang Niu · Masashi Sugiyama
Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional NetworksSitao Luan · Mingde Zhao · Xiao-Wen Chang · Doina Precup
Generalized Matrix Means for Semi-Supervised Learning with Multilayer GraphsPedro Mercado · Francesco Tudisco · Matthias Hein
Graph Agreement Models for Semi-Supervised LearningOtilia Stretcu · Krishnamurthy Viswanathan · Dana Movshovitz-Attias · Emmanouil Platanios · Sujith Ravi · Andrew Tomkins
Graph-Based Semi-Supervised Learning with Non-ignorable Non-responseFan Zhou · Tengfei Li · Haibo Zhou · Hongtu Zhu · Ye Jieping
HyperGCN: A New Method For Training Graph Convolutional Networks on HypergraphsNaganand Yadati · Madhav Nimishakavi · Prateek Yadav · Vikram Nitin · Anand Louis · Partha Talukdar
A Condition Number for Joint Optimization of Cycle-Consistent NetworksLeonidas J Guibas · Qixing Huang · Zhenxiao Liang
MixMatch: A Holistic Approach to Semi-Supervised LearningDavid Berthelot · Nicholas Carlini · Ian Goodfellow · Nicolas Papernot · Avital Oliver · Colin A Raffel
Uncoupled Regression from Pairwise Comparison DataLiyuan Xu · Junya Honda · Gang Niu · Masashi Sugiyama
Unlabeled Data Improves Adversarial RobustnessYair Carmon · Aditi Raghunathan · Ludwig Schmidt · John Duchi · Percy Liang