This paper introduces LDA-G, a scalable Bayesian approach to finding latent group structures in large real-world graph data. Existing Bayesian approaches for group discovery (suc...
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
Ioannis Tsamardinos, Constantin F. Aliferis, Alexa...
Increasingly advances in file carving, memory analysis and network forensics requires the ability to identify the underlying type of a file given only a file fragment. Work to dat...
To compare sample data from x-ray diffraction a suitable metric is developed to evaluate the similarity (or dissimilarity) between samples and to compare it to a references. The m...
George Runger, Kelly Canter, John Twist, David Ros...
Signal nding pattern discovery in unaligned DNA sequences is a fundamental problem in both computer science and molecular biology with important applications in locating regulator...