Abstract-- Pervasive Computing refers to a seamless and invisible computing environment which provides dynamic, proactive and context-aware services to the user by acquiring contex...
Learning visual models of object categories notoriously requires thousands of training examples; this is due to the diversity and richness of object appearance which requires mode...
Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
In this paper, we present an approach which, given a knowledge base and an appropriate text corpus, automatically induces patterns which can be used to query the knowledge base. W...
We propose a new method to program robots based on Bayesian inference and learning. It is called BRP for Bayesian Robot Programming. The capacities of this programming method are d...