Continuous-time Bayesian networks is a natural structured representation language for multicomponent stochastic processes that evolve continuously over time. Despite the compact r...
This paper addresses the problem of object detection and recognition in complex scenes, where objects are partially occluded. The approach presented herein is based on the hypothe...
Distributed Perception Networks (DPN) are a MAS approach to large scale fusion of heterogeneous and noisy information. DPN agents can establish meaningful information filtering c...
We examine the problem of overcoming noisy word-level alignments when learning tree-to-string translation rules. Our approach introduces new rules, and reestimates rule probabilit...
SybilInfer is an algorithm for labelling nodes in a social network as honest users or Sybils controlled by an adversary. At the heart of SybilInfer lies a probabilistic model of h...