This paper addresses the inference of probabilistic classification models using weakly supervised learning. In contrast to previous work, the use of proportion-based training data...
Carla Scalarin, Jacques Masse, Jean-Marc Boucher, ...
Traditional spectral classification has been proved to be effective in dealing with both labeled and unlabeled data when these data are from the same domain. In many real world ap...
The Web is now a huge information repository with a rich semantic structure that, however, is primarily addressed to human understanding rather than automated processing by a compu...
In categorial systems with a fixed structural component, the learning problem comes down to finding the solution for a set of typeassignment equations. A hard-wired structural co...
The main question addressed in the present work is how to find effectively a recursive function separating two sets drawn arbitrarily from a given collection of disjoint sets. I...