Greedy approaches to semi-supervised subspace learning

DOI10.1016/j.patcog.2014.10.031zbMath1374.68395OpenAlexW2043362806MaRDI QIDQ1678697

Min-Young Kim

Publication date: 20 November 2017

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2014.10.031

zbMATH Keywords

dimensionality reductionsemi-supervised learninginfinite-dim greedy search

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Related Items

Hierarchical unsupervised multi-view feature selection

Uses Software

• UCI-ml

Cites Work

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• Large margin subspace learning for feature selection
• A unified framework for semi-supervised dimensionality reduction
• Principal component analysis.
• On incremental and robust subspace learning
• Canonical Correlation Analysis: An Overview with Application to Learning Methods
• Laplacian Eigenmaps for Dimensionality Reduction and Data Representation