Efficient Sparse Representation for Learning With High-Dimensional Data

Due to the capability of effectively learning intrinsic structures from high-dimensional data, techniques based on sparse representation have begun to display an impressive impact on several fields, such as image processing, computer vision, and pattern recognition. Learning sparse representations i...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems Jg. 34; H. 8; S. 4208 - 4222
Hauptverfasser:	Chen, Jie, Yang, Shengxiang, Wang, Zhu, Mao, Hua
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.08.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Approximation algorithms Computational geometry Computer vision Constraints Convergence Convex functions Convexity Dictionaries Image processing Iterative algorithms Iterative methods Learning Linear representation low-dimensional structures Machine learning Optimization Pattern recognition probabilistic simplex Representations Sparse matrices sparse representation Sparsity Theoretical analysis
ISSN:	2162-237X, 2162-2388, 2162-2388
Online-Zugang:	Volltext
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