We propose a novel method of dimensionality reduction for supervised learning. Given a regression or classification problem in which we wish to predict a variable Y from an expla...
Kenji Fukumizu, Francis R. Bach, Michael I. Jordan
In this paper, we study dimension reduction of the three-dimensional (3D) Gross–Pitaevskii equation (GPE) modeling Bose–Einstein condensation under different limiting interact...
Weizhu Bao, Yunyi Ge, Dieter Jaksch, Peter A. Mark...
This work presents the use of sensor stream reduction algorithms in clustered wireless sensor networks (WSNs), where the cluster head node is responsible to reduce the amount of d...
We give a tutorial overview of several geometric methods for dimension reduction. We divide the methods into projective methods and methods that model the manifold on which the da...
In order to create a complete three-dimensional model of an object based on its two-dimensional images, the images have to be acquired from different views. An increasing number o...