With the advent of high throughput technologies, feature selection has become increasingly important in a wide range of scientific disciplines. We propose a new feature selection ...
Large amounts of remotely sensed data calls for data mining techniques to fully utilize their rich information content. In this paper, we study new means of discovery and summariz...
I present an expectation-maximization (EM) algorithm for principal component analysis (PCA). The algorithm allows a few eigenvectors and eigenvalues to be extracted from large col...
Semi-supervised clustering uses a small amount of supervised data to aid unsupervised learning. One typical approach specifies a limited number of must-link and cannotlink constra...
We consider the problem of document indexing and representation. Recently, Locality Preserving Indexing (LPI) was proposed for learning a compact document subspace. Different from...