Semi-supervised learning using ensembles of multiple 1D-embedding-based label boosting

DOI10.1142/S0219691316400014zbMath1334.68194MaRDI QIDQ2801845

Jian-zhong Wang

Publication date: 22 April 2016

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

zbMATH Keywords

interpolationregularizationsemi-supervised learningensemble1D multi-embeddinglabel boostingmultiple 1D embedding

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Related Items (5)

The performance of semi-supervised Laplacian regularized regression with the least square loss ⋮ Hyperspectral image classification using wavelet transform-based smooth ordering ⋮ Multiple one-dimensional embedding clustering scheme for hyperspectral image classification ⋮ A novel semi-supervised learning framework for hyperspectral image classification ⋮ 1D embedding multi-category classification methods

Uses Software

• SGTlight

Cites Work

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• Semi-supervised learning using multiple one-dimensional embedding based adaptive interpolation
• Harmonic Analysis of Digital Data Bases
• Dimensionality Reduction of Hyperspectral Imagery Data for FeatureClassification
• Understanding the Yarowsky Algorithm
• Generalized Tree-Based Wavelet Transform

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