Robust sparse coding via self-paced learning for data representation

DOI10.1016/j.ins.2020.08.097zbMath1475.68121OpenAlexW3082568708MaRDI QIDQ2055547

Xiaodong Feng, Sen Wu

Publication date: 1 December 2021

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2020.08.097

zbMATH Keywords

non-convex optimizationdata representationsparse codingself-paced learningnoisy corruption

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26) Learning and adaptive systems in artificial intelligence (68T05) Coding and information theory (compaction, compression, models of communication, encoding schemes, etc.) (aspects in computer science) (68P30)

Related Items (1)

Deep random walk of unitary invariance for large-scale data representation

Uses Software

• SLEP

Cites Work

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• Graph dual regularization non-negative matrix factorization for co-clustering
• A theoretical understanding of self-paced learning
• Least angle regression. (With discussion)
• Hyperplane-based nonnegative matrix factorization with label information
• Graph Regularized Sparse Coding for Image Representation

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