This paper proposes a multiple instance learning (MIL) algorithm for Gaussian processes (GP). The GP-MIL model inherits two crucial benefits from GP: (i) a principle manner of lea...
This paper presents and evaluates an approach to Bayesian model averaging where the models are Bayesian nets (BNs). Prior distributions are defined using stochastic logic programs...
Energy is increasingly a first-order concern in computer systems. Exploiting energy-accuracy trade-offs is an attractive choice in applications that can tolerate inaccuracies. Re...
Adrian Sampson, Werner Dietl, Emily Fortuna, Danus...
Robust execution of robotic tasks is a difficult problem. In many situations, these tasks involve complex behaviors combining different functionalities (e.g. perception, localizat...
Latest results of statistical learning theory have provided techniques such us pattern analysis and relational learning, which help in modeling system behavior, e.g. the semantics ...