Causality constraints of random discrete simulation make parallel and distributed processing difficult. Methods of applying reconfigurable logic to implement and accelerate simula...
Learning temporal causal graph structures from multivariate time-series data reveals important dependency relationships between current observations and histories, and provides a ...
Yan Liu 0002, Alexandru Niculescu-Mizil, Aurelie C...
Interruptions occur frequently in spontaneous conversations, and they are often associated with changes in the flow of conversation. Predicting interruption is essential in the d...
In this paper, we propose a novel method to localize (or track) a foreground object and segment the foreground object from the surrounding background with occlusions for a moving ...
We propose a data structure that decreases complexity of unsupervised competitive learning algorithms which are based on the growing cells structures approach. The idea is based on...