Structured sparsity regularized multiple kernel learning for Alzheimer’s disease diagnosis
Abstract
Multimodal data fusion has shown great advantages in uncovering information that could be overlooked by using single modality. In this paper, we consider the integration of high-dimensional multi-modality imaging and genetic data for Alzheimer’s disease (AD) diagnosis. With a focus on taking advantage of both phenotype and genotype information, a novel structured sparsity, defined by ℓ1, p-norm (p > 1), regularized multiple kernel learning...
Paper Details
Title
Structured sparsity regularized multiple kernel learning for Alzheimer’s disease diagnosis
Published Date
Apr 1, 2019
Journal
Volume
88
Pages
370 - 382
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