Abstract. We propose a dynamic process for network evolution, aiming at explaining the emergence of the small world phenomenon, i.e., the statistical observation that any pair of i...
Augustin Chaintreau, Pierre Fraigniaud, Emmanuelle...
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Taylor II is a menu-driven simulation package mainly used in manufacturing, warehousing, and material handling. It is developed for the analysis and quantitative evaluation of com...
In this paper we present a reference generation model based on Reference Domain Theory which gives a dynamic account of reference. This reference model assumes that each referring...
A novel framework is introduced for visual event detection. Visual events are viewed as stochastic temporal processes in the semantic concept space. In this concept-centered appro...