Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
Wireless sensor networks are rapidly finding their way through a plethora of new applications like precision farming and forestry, with increasing network scale, system complexit...
Taking a global analogy with the structure of perceptual biological systems, we present a system composed of two layers of real-valued sigmoidal neurons. The primary layer receives...
Statistical machine learning techniques for data classification usually assume that all entities are i.i.d. (independent and identically distributed). However, real-world entities...
-- Networks composed of large number of nodes interacting in structured ways such as power grids, communication networks, social networks or market networks are critical port of th...