We propose statistical learning methods for approximating implicit surfaces and computing dense 3D deformation fields. Our approach is based on Support Vector (SV) Machines, which...
This paper provides a comprehensive framework for the state space approach to Boolean networks. First, it surveys the authors' recent work on the topic: Using semitensor produ...
Mitigating the impact of computer failure is possible if accurate failure predictions are provided. Resources, applications, and services can be scheduled around predicted failure...
Abstract. Support Vector Machines Regression (SVMR) is a learning technique where the goodness of fit is measured not by the usual quadratic loss function (the mean square error),...
An algorithm for estimating the pose, i.e., translation and rotation, of an extended target object is introduced. Compared to conventional methods, where pose estimation is perfor...