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...
Traditionally, machine learning algorithms have been evaluated in applications where assumptions can be reliably made about class priors and/or misclassification costs. In this pa...
We propose STILL, a generic defense based on Static Taint and InitiaLization anaLyses, to detect exploit code embedded in data streams/requests targeting at various Internet servi...
This paper presents a power grid analyzer based on a random walk technique. A linear-time algorithm is first demonstrated for DC analysis, and is then extended to perform transien...
Haifeng Qian, Sani R. Nassif, Sachin S. Sapatnekar
This paper presents the result of an adaptive region growing segmentation technique for color document images using an irregular pyramid structure. The emphasis is in the segmentat...