Visual action recognition is an important problem in computer vision. In this paper, we propose a new method to probabilistically model and recognize actions of articulated object...
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
We present a novel approach to query reformulation which combines syntactic and semantic information by means of generalized Levenshtein distance algorithms where the substitution...
Amac Herdagdelen, Massimiliano Ciaramita, Daniel M...
We investigate the problem of modeling node capture attacks in heterogeneous wireless ad hoc and mesh networks. Classical adversarial models such as the Dolev–Yao model are know...
We study some mathematical programming formulations for the origin-destination model in airline revenue management. In particular, we focus on the traditional probabilistic model ...