5 papers · 1 filter
Hierarchical Multiple Kernel K-Means Algorithm Based on Sparse Connectivity
Lei Wang, Liang Du, Peng Zhou
Multiple kernel learning (MKL) aims to find an optimal, consistent kernel function. In the hierarchical multiple kernel clustering (HMKC) algorithm, sample features are extracted l…
Symmetry Nonnegative Matrix Factorization Algorithm Based on Self-paced Learning
Lei Wang, Liang Du, Peng Zhou +1
A symmetric nonnegative matrix factorization algorithm based on self-paced learning was proposed to improve the clustering performance of the model. It could make the model better…
Multiple Kernel Clustering via Local Regression Integration
Liang Du, Xin Ren, Haiying Zhang +1
Multiple kernel methods less consider the intrinsic manifold structure of multiple kernel data and estimate the consensus kernel matrix with quadratic number of variables, which ma…
Unsupervised feature selection algorithm framework based on neighborhood interval disturbance fusion
Xiaolin Lv, Liang Du, Peng Zhou +1
Feature selection technology is a key technology of data dimensionality reduction. Becauseof the lack of label information of collected data samples, unsupervised feature selection…
Fast Asymmetric Factorization for Large Scale Multiple Kernel Clustering
Yan Chen, Liang Du, Lei Duan
Kernel methods are extensively employed for nonlinear data clustering, yet their effectiveness heavily relies on selecting suitable kernels and associated parameters, posing challe…