We propose a generative statistical approach to human motion modeling and tracking that utilizes probabilistic latent semantic (PLSA) models to describe the mapping of image featu...
This paper proposes an efficient method to learn from multi source data with an Inductive Logic Programming method. The method is based on two steps. The first one consists in lea...
Crowdsourcing has recently become popular among machine learning researchers and social scientists as an effective way to collect large-scale experimental data from distributed w...
This paper is an exploration in a functional programming framework of isomorphisms between elementary data types (natural numbers, sets, finite functions, permutations binary deci...
This paper aims at formalizing the concept of learning rules from multisource data in a cardiac monitoring context. Our method has been implemented and evaluated on learning from d...