The ability to handle changes is a characteristic feature of successful software projects. The problem addressed in this paper is what should be done in project planning and itera...
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...
We propose statistical learning methods for approximating implicit surfaces and computing dense 3D deformation fields. Our approach is based on Support Vector (SV) Machines, which...
The research domain of aspect mining studies the problem of (semi-)automatically identifying potential aspects and crosscutting concerns in a software system, to improve the syste...
The exceptional growth of graphics hardware in programmability and data processing speed in the past few years has fuelled extensive research in using it for general purpose compu...