In this paper, we propose a general framework for distributed boosting intended for efficient integrating specialized classifiers learned over very large and distributed homogeneo...
In many practical domains, misclassification costs can differ greatly and may be represented by class ratios, however, most learning algorithms struggle with skewed class distrib...
William Klement, Peter A. Flach, Nathalie Japkowic...
This paper presents a model of neural network embodiment of intentions and planning mechanisms for autonomous agents. The model bridges the dichotomy of symbolic and non-symbolic ...
Reconstructing a person’s face from its skeletal remains is a task that has over many decades fascinated artist and scientist alike. In this paper we treat facial reconstruction ...
To explore the Perturb and Combine idea for estimating probability densities, we study mixtures of tree structured Markov networks derived by bagging combined with the Chow and Liu...
Sourour Ammar, Philippe Leray, Boris Defourny, Lou...