State space methods have proven indispensable in neural data analysis. However, common methods for performing inference in state-space models with non-Gaussian observations rely o...
Liam Paninski, Yashar Ahmadian, Daniel Gil Ferreir...
— Many methods exist for the automatic and optimal 3D reconstruction of camera motion and scene structure from image sequence (’Structure from Motion‘ or SfM). The solution t...
Many learning applications are characterized by high dimensions. Usually not all of these dimensions are relevant and some are redundant. There are two main approaches to reduce d...
Many problems in practically all fields of science, engineering and technology involve global optimization. It becomes more and more important to develop the efficient global opti...
In this paper we present the use of a previously developed single-objective optimization approach, together with the -constraint method, to provide an approximation of the Pareto ...