This paper addresses the issue of extraction of an academic researcher social network. By researcher social network extraction, we are aimed at finding, extracting, and fusing the...
Contextual information is important for sequence modeling. Hidden Markov Models (HMMs) and extensions, which have been widely used for sequence modeling, make simplifying, often u...
— One primary goal in rescue robotics is to deploy a team of robots for coordinated victim search after a disaster. This requires robots to perform subtasks, such as victim detec...
—Two probabilistic-based models, namely the Ensemble-Dependent Matrix model [1][3] and the Markov Random Field model [2], have been proposed to deal with faults in nanoscale syst...
Huifei Rao, Jie Chen, Changhong Yu, Woon Tiong Ang...
Markov Networks (also known as Markov Random Fields) have been proposed as a new approach to probabilistic modelling in Estimation of Distribution Algorithms (EDAs). An EDA employ...
Alexander E. I. Brownlee, John A. W. McCall, Deryc...