Manifold learning can discover the structure of high dimensional data and provides understanding of multidimensional patterns by preserving the local geometric characteristics. Ho...
Support vector machines (SVMs) have been promising methods for classification and regression analysis because of their solid mathematical foundations which convey several salient ...
Understanding the structure of multidimensional patterns, especially in unsupervised case, is of fundamental importance in data mining, pattern recognition and machine learning. Se...
Frequent subtree mining has attracted a great deal of interest among the researchers due to its application in a wide variety of domains. Some of the domains include bio informati...
With the proliferation of multimedia data and evergrowing requests for multimedia applications, new challenges are emerged for efficient and effective managing and accessing large...