In this paper, a novel two-tier Bayesian based method is proposed for hair segmentation. In the first tier, we construct a Bayesian model by integrating hair occurrence prior prob...
Dan Wang, Shiguang Shan, Wei Zeng, Hongming Zhang,...
We consider reinforcement learning as solving a Markov decision process with unknown transition distribution. Based on interaction with the environment, an estimate of the transit...
We present a fast, dynamic fault coverage estimation technique for sequential circuits that achieves high degrees of accuracy by signi cantly reducing the number of injected fault...
The FastInf C++ library is designed to perform memory and time efficient approximate inference in large-scale discrete undirected graphical models. The focus of the library is pro...
Ariel Jaimovich, Ofer Meshi, Ian McGraw, Gal Elida...
— The capacity of wireless multi-hop networks has been studied extensively in recent years. Most existing work tackles the problem from an asymptotic perspective and assumes a si...