Correlation clustering is a type of clustering that uses a basic form of input data: For every pair of data items, the input specifies whether they are similar (belonging to the s...
This work achieves full registration of scenes in a large area and creates visual indexes for visualization in a digital city. We explore effective mapping, indexing, and display ...
Background: Ensemble attribute profile clustering is a novel, text-based strategy for analyzing a userdefined list of genes and/or proteins. The strategy exploits annotation data ...
J. R. Semeiks, A. Rizki, Mina J. Bissell, I. Saira...
Testability is one of the most important factors that are considered during design cycle along with reliability, speed, power consumption, cost and other factors important for a c...
We develop new techniques for time series classification based on hierarchical Bayesian generative models (called mixed-effect models) and the Fisher kernel derived from them. A k...