Semi-supervised learning using autodidactic interpolation on sparse representation-based multiple one-dimensional embedding

DOI10.1142/S0219691319500139zbMath1410.68314OpenAlexW2906773961MaRDI QIDQ5379794

Chao Ma, Chuanwu Yang, Hao Deng, Li-Jun Shen

Publication date: 14 June 2019

Published in: International Journal of Wavelets, Multiresolution and Information Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/s0219691319500139

zbMATH Keywords

sparse representationsemi-supervised learningautodidactic interpolation schemeone-dimensional embedding

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (2)

Semi-supervised partial least squares ⋮ Hyperspectral image classification using wavelet transform-based smooth ordering

Uses Software

• Concorde

Cites Work

• Semi-supervised clustering with metric learning: an adaptive kernel method
• A decision-theoretic generalization of on-line learning and an application to boosting
• Support-vector networks
• Semi-supervised learning using multiple one-dimensional embedding based adaptive interpolation
• Face recognition via collaborative representation based multiple one-dimensional embedding
• 1D embedding multi-category classification methods
• Minimum Error Entropy Based Sparse Representation for Robust Subspace Clustering
• Image Processing Using Smooth Ordering of its Patches
• Random forests
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