We present a distributed machine learning framework based on support vector machines that allows classification problems to be solved iteratively through parallel update algorithm...
This paper describes an attempt to devise a knowledge discovery model that is inspired from the two theoretical frameworks of selectionism and constructivism in human cognitive le...
For automatic semantic annotation of large-scale video database, the insufficiency of labeled training samples is a major obstacle. General semi-supervised learning algorithms can...
An anytime algorithm is capable of returning a response to the given task at essentially any time; typically the quality of the response improves as the time increases. Here, we c...
In this paper a learning based local search approach for propositional satisfiability is presented. It is based on an original adaptation of the conflict driven clause learning ...
Gilles Audemard, Jean-Marie Lagniez, Bertrand Mazu...