A serious problem in learning probabilistic models is the presence of hidden variables. These variables are not observed, yet interact with several of the observed variables. As s...
Gal Elidan, Noam Lotner, Nir Friedman, Daphne Koll...
Being the de-facto standard (object-oriented-OO) method(-logy) for software-intensive systems development, UML with its different diagrams and supporting tools represent nowadays t...
In this paper we present a novel framework for evolving ART-based classification models, which we refer to as MOME-ART. The new training framework aims to evolve populations of ART...
Rong Li, Timothy R. Mersch, Oriana X. Wen, Assem K...
As an alternative to expensive road surveys, we are working toward a method to infer the road network from GPS data logged from regular vehicles. One of the most important componen...
Abstract. In distributed computer networks where resources are under decentralized control, selfish users will generally not work towards one common goal, such as maximizing the o...