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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Vydáno v:	IEEE transaction on neural networks and learning systems Ročník 34; číslo 8; s. 4208 - 4222
Hlavní autoři:	Chen, Jie, Yang, Shengxiang, Wang, Zhu, Mao, Hua
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States IEEE 01.08.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	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
On-line přístup:	Získat plný text
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