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- research-articleDecember 2023
Simple multiple kernel k-means with kernel weight regularization
AbstractMultiple kernel clustering (MKC) aims to determine the optimal kernel from several pre-computed basic kernels. Most of MKC algorithms follow a common assumption that the optimal kernel is linearly combined by basic kernels. Based on a min–max ...
Highlights- A novel module encourages more kernels participating in the min–max optimization.
- The sparsity of kernel weight helps balance between the adaptive kernel and average one.
- We have designed an efficient and effective algorithm with ...
- research-articleNovember 2023
Mutual structure learning for multiple kernel clustering
Information Sciences: an International Journal (ISCI), Volume 647, Issue Chttps://doi.org/10.1016/j.ins.2023.119445AbstractMultiple kernel clustering (MKC) has garnered considerable attention in recent years, aiming to obtain an optimal partition from multiple base kernels. Existing MKC methods typically focus on either learning the pairwise structure by ...