Abstract. Research works and surveys focusing on e-Government Digital Services availability and usage, reveal that often services are available but ignored by citizens. In our hypo...
Flavio Corradini, Damiano Falcioni, Andrea Polini,...
We present a learning framework for Markovian decision processes that is based on optimization in the policy space. Instead of using relatively slow gradient-based optimization al...
Abstract –In this paper, a variational message passing framework is proposed for Markov random fields, which is computationally more efficient and admits wider applicability comp...
To exactly detect what events occur in baseball games, a framework that integrates rule-based and model-based decision methods is proposed. The rule-based decision module infers w...
This paper describes a method for the segmentation of dynamic data. It extends well known algorithms developed in the context of static clustering (e.g., the c-means algorithm, Ko...