We propose a new method of classifying documents into categories. We define for each category a finite mixture model based on soft clustering of words. We treat the problem of cla...
In an attempt to overcome problems associated with articulatory limitations and generative models, this work considers the use of phonological features in discriminative models fo...
This paper adresses the problem of anomaly detection and classification by using a noisy measurement vector corrupted by some linear unknown nuisance parameters. An invariant con...
We address the problem of integrating documents from different sources into a master catalog. This problem is pervasive in web marketplaces and portals. Current technology for aut...
We present an application of multi-objective evolutionary optimization of feed-forward neural networks (NN) to two real world problems, car and face classification. The possibly co...