Multiple kernel clustering with late fusion consensus local graph preserving
Sign Up to like & getrecommendations! Published in 2021 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.22596
Abstract: Multiple kernel clustering (MKC) methods aim at integrating an optimal partition from a set of precalculated kernel matrices. Though achieving success in various applications, we observe that existing MKC methods: (i) lack of representation flexibility;… read more here.
Keywords: local graph; kernel clustering; multiple kernel; graph ... See more keywords
Optimal Neighborhood Multiple Kernel Clustering With Adaptive Local Kernels
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2020.3014104
Abstract: Multiple kernel clustering (MKC) algorithm aims to group data into different categories by optimally integrating information from a group of pre-specified kernels. Though demonstrating superiorities in various applications, we observe that existing MKC algorithms usually… read more here.
Keywords: optimal neighborhood; adaptive local; multiple kernel; kernel clustering ... See more keywords
Ising-Based Kernel Clustering
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DOI: 10.3390/a16040214
Abstract: Combinatorial clustering based on the Ising model is drawing attention as a high-quality clustering method. However, conventional Ising-based clustering methods using the Euclidean distance cannot handle irregular data. To overcome this problem, this paper proposes an… read more here.
Keywords: matrix; based kernel; ising based; kernel clustering ... See more keywords
Local Sample-weighted Multiple Kernel Clustering with Consensus Discriminative Graph
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
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