Distributional analysis is widely used to study social choice in Euclidean models [35, 36, 1, 5, 11, 19, 8, 2, e.g]. This method assumes a continuum of voters distributed accordin...
We propose a novel statistical approach to detect defects in digitized archive film by using temporal information across a number of frames modeled with an HMM. The HMM is traine...
Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...
We present a generative model approach to explore intrinsic semantic structures in sport videos, e.g., the camera view in American football games. We will invoke the concept of se...
Knowledge about the workload is an important aspect for scheduling of resources as parallel computers or Grid components. As the scheduling quality highly depends on the character...