A self-organizing neural network for learning and recall of complex temporal sequences is proposed. we consider a single sequence with repeated items, or several sequences with a c...
Abstract. This paper describes an experimental comparison between two standard supervised learning methods, namely Naive Bayes and Exemplar–basedclassification, on the Word Sens...
We present an approach for recovering articulated body pose from single monocular images using the Specialized Mappings Architecture (SMA), a non-linear supervised learning archit...
Model selection is important in many areas of supervised learning. Given a dataset and a set of models for predicting with that dataset, we must choose the model which is expected...
In this paper, we propose a novel solution for multi-view object detection. Given a set of training examples at different views, we select examples at a few key views and train on...