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The study of networked systems has experienced a particular surge of interest in the last decade. One issue that has received a considerable amount of attention is the detection and characterization of community structure in networks, meaning the appearance of densely connected groups of vertices, with only sparser connections between groups. In this paper, we present an approach for the problem of...
The typical classification rule for kernel sparse representation-based classifier (KSRC) is the reconstruction error minimization rule. Its computational complexity mainly depends on both the dimensionality of a subspace and the number of training samples. This paper presents an alternative classification rule, called reconstruction coefficient energy maximization, for KSRC and applies it to target...
Piecewise vector quantized approximation (PVQA) is a dimensionality reduction technique for time series data mining, which adopts the closet codeword stemming from a codebook of time subsequences with equal length to represent the long time series. This paper proposes a multi-codebook piecewise vector quantized approximation (MCPVQA), in which we generate a codebook for each class using PVQA on considering...
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