We consider the problem of fitting a large-scale covariance matrix to multivariate Gaussian data in such a way that the inverse is sparse, thus providing model selection. Beginnin...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...
The increasing number of independent IEEE 802.11 WLANs owned and managed by autonomous users has led to increased interference, resulting in performance degradation and unfairness...
Abstract. Navigating consists of coordinating egocentric and allocentric spatial frames of reference. Virtual environments have afforded researchers in the spatial community with ...
Mathieu Simonnet, Dan Jacobson, Stephane Vieillede...
Abstract— We present a machine learning approach for trajectory inverse kinematics: given a trajectory in workspace, to find a feasible trajectory in angle space. The method lea...
Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...