We present a set of techniques and design principles for the visualization of large dynamic software logs consisting of attributed change events, such as obtained from instrumenti...
We present a novel clustering method using HMM parameter space and eigenvector decomposition. Unlike the existing methods, our algorithm can cluster both constant and variable leng...
Background: Protein interactions support cell organization and mediate its response to any specific stimulus. Recent technological advances have produced large data-sets that aim ...
—Motivated by the fact that most of the existing QoS service composition solutions have limited scalability, we develop a hierarchical-based solution framework to achieve scalabi...
Jingwen Jin, Jin Liang, Jingyi Jin, Klara Nahrsted...
We present a hierarchical generative model for object recognition that is constructed by weakly-supervised learning. A key component is a novel, adaptive patch feature whose width...