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...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	IEEE transaction on neural networks and learning systems Ročník 34; číslo 8; s. 4208 - 4222
Hlavní autori:	Chen, Jie, Yang, Shengxiang, Wang, Zhu, Mao, Hua
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.08.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	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 prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!