IEEE

Improved Symmetric and Nonnegative Matrix Factorization Models for Undirected, Sparse and Large-Scaled Networks: A Triple Factorization-Based Approach

Abstract: Undirected, sparse and large-scaled networks existing ubiquitously in practical engineering are vitally important since they usually contain rich information in various patterns. Matrix ...
IEEE

Semi-Supervised Symmetric Non-Negative Matrix Factorization With Low-Rank Tensor Representation

Abstract: Semi-supervised symmetric non-negative matrix factorization (SNMF) utilizes the available supervisory information (usually in the form of pairwise constraints) to improve the clustering ...