We propose a new approach for learning Bayesian classifiers from data. Although it relies on traditional Bayesian network (BN) learning algorithms, the effectiveness of our approa...
Support Vector Machines (SVMs) have been applied to solve the classification of volatile organic compounds (VOC) data in some recent studies. SVMs provide good generalization perfo...
Backpropagation, similar to most learning algorithms that can form complex decision surfaces, is prone to overfitting. This work presents classification-based objective functions, ...
Regulatory cascades consisting of stress-induced gene modules and their transcriptional regulators were recently identified and quantitatively modeled using Artificial Neural Netwo...
We propose a new method for solving structured CSPs which generalizes and improves the Cyclic-Clustering approach [4]. First, the cutset and the tree-decomposition of the constrai...