Local Sample-weighted Multiple Kernel Clustering with Consensus Discriminative Graph
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DOI: 10.48550/arxiv.2207.02846
Abstract: Multiple kernel clustering (MKC) is committed to achieving optimal information fusion from a set of base kernels. Constructing precise and local kernel matrices is proven to be of vital significance in applications since the unreliable… read more here.
Keywords: local sample; multiple kernel; kernel clustering; consensus discriminative ... See more keywords