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This paper investigates the salient machine faults representation-based classification issue by dictionary learning. A novel structured latent label consistent dictionary learning (LLC-DL) model is proposed for joint discriminative salient representation and classification. Our LLC-DL deals with the tasks by solving one objective function that aims to minimize the structured reconstruction error,...
The problem of semi-supervised dimensionality reduction with kernels called KS2DR is considered for semi-supervised learning. In this setting, domain knowledge in the form of pair constraints is adopted to specify whether pairs of instances belong to the same class or not. KS2DR can project the samples data onto a set of `useful' features and preserve the structure of unlabeled samples data as well...
Inspired by natural immune systems, Artificial Immune System (AIS) is an emerging kind of computational intelligence paradigm. The traditional immune algorithm and Ai-net for clustering still have the problems of training time-consumption and accuracy. In this paper, AIS Algorithm is improved with Quantum Mechanics theory and the Schro??dinger equation to add the idea of the energy level into the...
The objection of the standard support vector machine (SVM) is to achieve the maximum margin and control the generalization capability of SVM classifier. It only considers the punishment constraints, but does not introduce the within-class and between-class constraint projections. A novel robust discriminative support vector machines algorithm with pairwise constraint projections called CPSVM is discussed...
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