Various supervised inference methods can be analyzed as convex duals of the generalized maximum entropy (MaxEnt) framework. Generalized MaxEnt aims to find a distribution that max...
This paper introduces a semi-supervised distance metric learning algorithm which uses pair-wise equivalence (similarity and dissimilarity) constraints to improve the original dist...
In this paper, we present a regularization approach on discrete graph spaces for perceptual image segmentation via semisupervised learning. In this approach, first, a spectral cl...
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, ...
This paper investigates a new approach for training discriminant classifiers when only a small set of labeled data is available together with a large set of unlabeled data. This a...