Aug 2, 2024 · We propose a novel graph learning method, termed consensus local graph based on MKL (CLGMKL), for clustering.
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Jul 5, 2022 · This paper proposes a novel local sample-weighted multiple kernel clustering (LSWMKC) model. We first construct a consensus discriminative affinity graph in ...
A novel method, termed as consensus graph learning based on local kernels (CGLLK), is introduced. CGLLK is based on the partitions extracted by kernel k-means.
To alleviate such problems, this article proposes a novel local sample-weighted MKC (LSWMKC) model. We first construct a consensus discriminative affinity graph ...
Jul 25, 2021 · In this paper, we propose a novel method, multiple kernel clustering algorithm with late fusion local graph preserving (MKC‐LFLGP). As shown in ...
A simple connected undirected graph GG is called a clustering coefficient locally maximizing graph if its clustering coefficient is not less than that of any ...
Aug 31, 2021 · In this paper, we propose a late fusion MKC method with local graph refinement to address the aforementioned issues.
Jul 20, 2020 · In this article, we propose a novel pure graph-based MKC method. Specifically, a new graph model is proposed to preserve the local manifold structure of the ...
Overall, kernel k-means (KKM) and spectral clustering (SC) are two basic methods used for MKC. KKM-based MKC methods usually learn a consensus ker- nel by ...
Specifically, we first design a simple yet effective scheme to construct the local kernels of base kernels and then a consensus graph is applied to capture the ...