In this paper, we propose a probabilistic framework targeting three important issues in the computation of quality and trust in decentralized systems. Specifically, our approach a...
Abstract. Many computer protection tools incorporate learning techniques that build mathematical models to capture the characteristics of system's activity and then check whet...
Increasing demand for power-efficient, high-performance computing requires tuning applications and/or the underlying hardware to improve the mapping between workload heterogeneity...
We present a data-driven approach to learn user-adaptive referring expression generation (REG) policies for spoken dialogue systems. Referring expressions can be difficult to unde...
Affective and human-centered computing have attracted a lot of attention during the past years, mainly due to the abundance of devices and environments able to exploit multimodal i...