Abstract. Kernel based methods (such as k-nearest neighbors classifiers) for AI tasks translate the classification problem into a proximity search problem, in a space that is usu...
—The conventional K-Means clustering algorithm must know the number of clusters in advance and the clustering result is sensitive to the selection of the initial cluster centroid...
Jing Xiao, YuPing Yan, Ying Lin, Ling Yuan, Jun Zh...
—This paper applies the Differential Evolution (DE) algorithm to the task of automatic fuzzy clustering in a Multi-objective Optimization (MO) framework. It compares the performa...
Microarray technology produces large amounts of information to be manipulated by analysis methods, such as biclustering algorithms, to extract new knowledge. All-purpose multivaria...
Motivated by the needs for efficient indexing structures adapted to real applications in video database, we present a new indexing structure named Kpyr. In Kpyr, we use a clusteri...