Semi-supervised learning aims at taking advantage of unlabeled data to improve the efficiency of supervised learning procedures. For discriminative models however, this is a chall...
Abstract. This paper presents a model for the probability of correct classification for the Cooperative Modular Neural Network (CMNN). The model enables the estimation of the perf...
In this paper, we introduce a new instance-based approach to the label ranking problem. This approach is based on a probability model on rankings which is known as the Mallows mode...
Dynamic Probabilistic Networks (DPNs) are exploited for modelling the temporal relationships among a set of different object temporal events in the scene for a coherent and robust...
In this paper we present a new framework for image segmentation using probabilistic multinets. We apply this framework to integration of regionbased and contour-based segmentation ...