Compressed labeling on distilled labelsets for multi-label learning
type: Item
instance of: scholarly article
title: Compressed labeling on distilled labelsets for multi-label learning
zbMATH Open document ID: 1243.68259
author: Tianyi Zhou
author: Dacheng Tao
author: Xindong Wu
published in: Machine Learning
publication date: 2012-07-31T00:00:00Z
Mathematics Subject Classification ID: 68T05
Mathematics Subject Classification ID: 62H30
zbMATH DE Number: 6062648
zbMATH Keywords: multi-label prediction
zbMATH Keywords: labelset selection
zbMATH Keywords: compressed sensing
zbMATH Keywords: random projection
zbMATH Keywords: label compression
zbMATH Keywords: distilled labelsets
zbMATH Keywords: binary matrix decomposition
zbMATH Keywords: KL divergence
zbMATH Keywords: hypothesis test of distribution
zbMATH Keywords: support vector machines
describes a project that uses: MULAN
describes a project that uses: ML-KNN
describes a project that uses: SMOTE
describes a project that uses: ElemStatLearn
describes a project that uses: LIBSVM
describes a project that uses: BoosTexter
describes a project that uses: NESVM
MaRDI profile type: Publication
full work available at URL: s10994-011-5276-1
OpenAlex ID: W2038857347
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DOI: 10.1007/S10994-011-5276-1
description: scientific article; zbMATH DE number 6062648