Constrained large margin local projection algorithms and extensions for multimodal dimensionality reduction

DOI10.1016/j.patcog.2012.05.015zbMath1248.68426OpenAlexW2088349130MaRDI QIDQ454445

Tommy W. S. Chow, Mingbo Zhao, Zhao Zhang

Publication date: 5 October 2012

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

Full work available at URL: https://doi.org/10.1016/j.patcog.2012.05.015

zbMATH Keywords

pattern classificationkernel methoddimensionality reductionpairwise constraintslarge margin projectionlocality preservationmanifold visualizationmultimodality preservation

Mathematics Subject Classification ID

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

Related Items (5)

Robust dimensionality reduction via feature space to feature space distance metric learning ⋮ Regularized linear discriminant analysis via a new difference-of-convex algorithm with extrapolation ⋮ Marginal semi-supervised sub-manifold projections with informative constraints for dimensionality reduction and recognition ⋮ Semi-supervised double sparse graphs based discriminant analysis for dimensionality reduction ⋮ Similarity preserving low-rank representation for enhanced data representation and effective subspace learning

Uses Software

• KPCA plus LDA

Cites Work

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• Class label versus sample label-based CCA
• Graph-optimized locality preserving projections
• Bagging constraint score for feature selection with pairwise constraints
• Non-linear metric learning using pairwise similarity and dissimilarity constraints and the geometrical structure of data
• Face recognition using discriminant locality preserving projections based on maximum margin criterion
• Constraint score: A new filter method for feature selection with pairwise constraints
• Orthogonal neighborhood preserving discriminant analysis for face recognition
• A generalized Foley–Sammon transform based on generalized fisher discriminant criterion and its application to face recognition
• Canonical Correlation Analysis: An Overview with Application to Learning Methods
• Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
• Discrete Cosine Transform

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