We study a generative model in which hidden causes combine competitively to produce observations. Multiple active causes combine to determine the value of an observed variable thr...
The Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent parame...
A new quasi-Newton scheme for updating a low rank positive semi-definite Hessian approximation is described, primarily for use in sequential quadratic programming methods for non...
In this paper we propose a rigorous framework for texture image segmentation relying on region-based active contours (RBAC) and sparse texture representation. Such representations...
We investigate the use of linear and nonlinear principal manifolds for learning low-dimensional representations for visual recognition. Three techniques: Principal Component Analy...