Theefficiency of algorithmsfor probabilistic inference in Bayesian networks can be improvedby exploiting independenceof causal influence. Thefactorized representation of independe...
Based on the theory of Markov Random Fields, a Bayesian regularization model for diffusion tensor images (DTI) is proposed in this paper. The low-degree parameterization of diffus...
Siming Wei, Jing Hua, Jiajun Bu, Chun Chen, Yizhou...
Belief propagation is widely used in inference of graphical models. It yields exact solutions when the underlying graph is singly connected. When the graph contains loops, double-c...
In this paper, we propose and investigate a new user scenario for face annotation, in which users are allowed to multi-select a group of photographs and assign names to these phot...
Lei Zhang, Yuxiao Hu, Mingjing Li, Wei-Ying Ma, Ho...
This paper deals with the multi-agent patrolling problem in unknown environment using two collective approaches exploiting environmental dynamics. After specifying criteria of per...
Hoang Nam Chu, Arnaud Glad, Olivier Simonin, Fran&...