Probabilistic mixture models are used for a broad range of data analysis tasks such as clustering, classification, predictive modeling, etc. Due to their inherent probabilistic na...
Abstract-- This paper proposes a novel framework for describing articulated robot kinematics motion with the goal of providing a unified representation by combining symbolic or qua...
This paper addresses the challenge of recognizing behavior of groups of individuals in unconstraint surveillance environments. As opposed to approaches that rely on agglomerative ...
Background: The discovery of cis-regulatory modules in metazoan genomes is crucial for understanding the connection between genes and organism diversity. It is important to quanti...
Saurabh Sinha, Mark D. Schroeder, Ulrich Unnerstal...
Concurrent programming languages are growing in importance with the advent of multi-core systems. However, concurrent programs suffer from problems, such as data races and deadloc...