Abstracts "Mixtures at the Interface" David Scott, Rice University Mixture modeling provides an effective framework for complex, high-dimensional data. The potential of m...
Although most of existing research usually detects events by analyzing the content or structural information of Web documents, a recent direction is to study the usage data. In th...
In this paper we present a face recognition method based on multiway analysis of color face images, which is robust to varying illumination conditions. Illumination changes cause l...
Robustly tracking moving objects in video sequences is one of the key problems in computer vision. In this paper we introduce a computationally efficient nonlinear kernel learning...
Chunhua Shen, Anton van den Hengel, Michael J. Bro...
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...