Most existing subspace analysis-based tracking algorithms utilize a flattened vector to represent a target, resulting in a high dimensional data learning problem. Recently, subspa...
Xi Li, Weiming Hu, Zhongfei Zhang, Xiaoqin Zhang, ...
Polynomial chaos theory (PCT) has been proven to be an efficient and effective way to represent and propagate uncertainty through system models and algorithms in general. In partic...
Window Abstraction for Infinite Markov Chains Thomas A. Henzinger1 , Maria Mateescu1 , and Verena Wolf1,2 1 EPFL, Switzerland 2 Saarland University, Germany Abstract. We present an...
Especially in dynamic environments a key feature concerning the robustness of mobile robot navigation is the capability of global self-localization. This term denotes a robot'...
This paper presents a new deterministic approximation technique in Bayesian networks. This method, "Expectation Propagation," unifies two previous techniques: assumed-de...