
Learning from SimilarityConfidence Data
Weakly supervised learning has drawn considerable attention recently to ...
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Provable Defense Against Delusive Poisoning
Delusive poisoning is a special kind of attack to obstruct learning, whe...
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MetaInfoNet: Learning TaskGuided Information for Sample Reweighting
Deep neural networks have been shown to easily overfit to biased trainin...
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SemiNLL: A Framework of NoisyLabel Learning by SemiSupervised Learning
Deep learning with noisy labels is a challenging task. Recent prominent ...
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Pointwise Binary Classification with Pairwise Confidence Comparisons
Ordinary (pointwise) binary classification aims to learn a binary classi...
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COMET: Convolutional Dimension Interaction for Deep Matrix Factorization
Latent factor models play a dominant role among recommendation technique...
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GLIMG: Global and Local Item Graphs for TopN Recommender Systems
Graphbased recommendation models work well for topN recommender system...
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Provably Consistent PartialLabel Learning
Partiallabel learning (PLL) is a multiclass classification problem, wh...
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Incorporating Multiple Cluster Centers for MultiLabel Learning
Multilabel learning deals with the problem that each instance is associ...
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Learning Crossdomain SemanticVisual Relation for Transductive ZeroShot Learning
ZeroShot Learning (ZSL) aims to learn recognition models for recognizin...
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Combating noisy labels by agreement: A joint training method with coregularization
Deep Learning with noisy labels is a practically challenging problem in ...
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Progressive Identification of True Labels for PartialLabel Learning
Partiallabel learning is one of the important weakly supervised learnin...
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Learning from Multiple Complementary Labels
Complementarylabel learning is a new weaklysupervised learning framewo...
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A distributionfree smoothed combination method of biomarkers to improve diagnostic accuracy in multicategory classification
Results from multiple diagnostic tests are usually combined to improve t...
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Collaboration based MultiLabel Learning
It is wellknown that exploiting label correlations is crucially importa...
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Partial Label Learning with SelfGuided Retraining
Partial label learning deals with the problem where each training instan...
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Lei Feng
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