Abstract. We propose a method of unsupervised learning from stationary, vector-valued processes. A low-dimensional subspace is selected on the basis of a criterion which rewards da...
In this paper we describe a method that estimates the motion of a calibrated camera (settled on an experimental vehicle) and the tridimensional geometry of the environment. The on...
E. Mouragnon, Fabien Dekeyser, Patrick Sayd, Maxim...
— A framework that describes the evolution of P systems with bounded parallelism is defined by introducing basic formal features that can be then integrated into a structural op...
A new approach to the induction of multivariate decision trees is proposed. A linear decision function (hyper-plane) is used at each non-terminal node of a binary tree for splittin...
The standard 2-norm SVM is known for its good performance in twoclass classi£cation. In this paper, we consider the 1-norm SVM. We argue that the 1-norm SVM may have some advanta...
Ji Zhu, Saharon Rosset, Trevor Hastie, Robert Tibs...