Classification algorithms typically induce population-wide models that are trained to perform well on average on expected future instances. We introduce a Bayesian framework for l...
To recognize people by their gait from a sequence of images, we have proposed a statistical approach which combined eigenspace transformation (EST) with canonical space transforma...
This paper proposes and evaluates the k-greedy equivalence search algorithm (KES) for learning Bayesian networks (BNs) from complete data. The main characteristic of KES is that i...
Abstract--Cloud computing infrastructures are providing resources on demand for tackling the needs of large-scale distributed applications. Determining the amount of resources to a...
This paper describes the study conducted to design and evaluate a two-level on-line scheduler to dynamically schedule a stream of sequential and multi-threaded batch jobs on large...
Marco Pasquali, Ranieri Baraglia, Gabriele Capanni...