A generalized adaptive robust distance metric driven smooth regularization learning framework for pattern recognition

•A novel generalized adaptive robust distance metric is presented, called Lδ(u).•The Lδ(u) has some desirable salient properties, such as symmetry, boundedness, robustness, nonconvexity, and adaptivity, with both first-order and higher-order moments from samples.•The Lδ(u) can pick different robust...

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Vydáno v:	Signal processing Ročník 211; s. 109102
Hlavní autoři:	Ma, Jun, Yu, Guolin
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 01.10.2023
Témata:	DC programming algorithm Generalized adaptive robust distance metric Manifold regularization Newton-Armijo algorithm Robust classification Twin extreme learning machine DC programming algorithm Robust classification Twin extreme learning machine Manifold regularization Generalized adaptive robust distance metric Newton-Armijo algorithm
ISSN:	0165-1684, 1872-7557
On-line přístup:	Získat plný text
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