Graph optimization for dimensionality reduction with sparsity constraints

DOI10.1016/J.PATCOG.2011.08.015zbMath1227.68097OpenAlexW2123961273MaRDI QIDQ650966

Lishan Qiao, Song-can Chen, Li-mei Zhang

Publication date: 7 December 2011

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

Full work available at URL: https://doi.org/10.1016/j.patcog.2011.08.015

zbMATH Keywords

face recognitiondimensionality reductionsparse representationgraph construction

Mathematics Subject Classification ID

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

Related Items (8)

Double linear regressions for single labeled image per person face recognition ⋮ On group-wise \(\ell_p\) regularization: theory and efficient algorithms ⋮ Low-rank and sparse embedding for dimensionality reduction ⋮ Large margin subspace learning for feature selection ⋮ Projected fuzzy C-means with probabilistic neighbors ⋮ Linear regression based projections for dimensionality reduction ⋮ Constrained large margin local projection algorithms and extensions for multimodal dimensionality reduction ⋮ Adaptive graph construction using data self-representativeness for pattern classification

Uses Software

• SLEP

Cites Work

• Sparsity preserving projections with applications to face recognition
• Graph-optimized locality preserving projections
• Least angle and \(\ell _{1}\) penalized regression: a review
• Semi-supervised orthogonal discriminant analysis via label propagation
• A generalized Foley–Sammon transform based on generalized fisher discriminant criterion and its application to face recognition
• Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
• Convergence of a block coordinate descent method for nondifferentiable minimization

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