Incomplete Multi-view Clustering via Graph Regularized Matrix FactorizationMulti-view clusteringIncomplete viewCommon latent representationOut-of-sampleClustering with incomplete views is a challenge in multiview clustering. In this paper, we provide a novel and simple method to address this issue. ...
Graph regularized non-negative matrix factorization by maximizing correntropy. arXiv preprint arXiv:1405.2246, 2014.Li, L., Yang, J., Zhao, K., Xu, Y., Zhang, H., Fan, Z.: Graph regularized non-negative matrix factorization by maximizing correntropy. arXiv preprint arXiv:1405.2246 (2014)...
Zheng ZhangThe University of QueenslandYong XuHarbin Institute of Technology, ShenzhenZuofeng ZhongHarbin Institute of Technology, ShenzhenSpringer, ChamWen, J.; Zhang, Z.; Xu, Y.; and Zhong, Z. 2018c. Incomplete multi-view clustering via graph regularized matrix factoriza- tion. arXiv ...
proposed a computational model, dual-network sparse graph regularized matrix factorization (DNSGRMF), for predicting miRNA–disease associations by integrating the miRNA functional similarity matrix, the disease semantic similarity matrix and Gaussian kernel similarities with the addition of the L2,1 norm...
3 Graph Regularized Non-negative Matrix Factorization By using the non-negative constraints, NMF can learn a parts-based representation. However, NMF per- forms this learning in the Euclidean space. It fails to to discover the intrinsic geometrical and discriminating structure of the data space, wh...
We further propose two refined-graph regularized nonnegative matrix factorization methods and use them to perform image clustering. Experimental results on several image datasets reveal that they outperform 11 representative methods.XUELONG LIChinese Academy of SciencesGUOSHENG CUI...
Guan NN, Zhao Y, Wang CC, Li JQ, Chen X, Piao X. Anticancer drug response prediction in cell lines using weighted graph regularized matrix factorization. Mol Ther Nucleic Acids. 2019;17:164–74.. Cao S, Lu W, Xu Q. Grarep: Learning graph representations with global structural information...
In this paper, we propose a new novel framework of Evolutionary Clustering based on Graph regularized Nonnegative Matrix Factorization (ECGNMF), to detect dynamic communities and the evolution patterns and predict the varying structure across the temporal networks. More concretely, we construct a ...
Graph Regularized Nonnegative Matrix Factorization for Data Representation Deng Cai Xiaofei He Jiawei...
In this paper, we discuss multi-view clustering based on graph-regularized nonnegative matrix factorization with fusing useful information effectively to improve recognition accuracy. Useful information is enhanced via graph embedding, and redundant information is removed using the orthogonal constraint in ...