Distance metric is widely used in similarity estimation. In this paper we find that the most popular Euclidean and Manhattan distance may not be suitable for all data distribution...
Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
Motivation: Genome maps are fundamental to the study of an organism and essential in the process of genome sequencing which in turn provides the ultimate map of the genome. The in...
Thomas Faraut, Simon de Givry, Patrick Chabrier, T...
This paper considers the estimation of shooter locations using a sensor network where each sensor measures the time difference between receptions of a firearm's muzzle blast ...
Data collected through a recent web-based survey show that the perception (i.e. labeling) of a human facial expression by a human observer is a subjective process, which results i...
Matteo Sorci, Jean-Philippe Thiran, J. Cruz, T. Ro...