Abstract. This paper describes a novel approach to recovering a parametric deformation that optimally registers one image to another. The method proceeds by constructing a global c...
We consider principal component analysis (PCA) in decomposable Gaussian graphical models. We exploit the prior information in these models in order to distribute its computation. ...
Scheduling large amounts of tasks in distributed computing platforms composed of millions of nodes is a challenging goal, even more in a fully decentralized way and with low overhe...
Maji and Berg [13] have recently introduced an explicit feature map approximating the intersection kernel. This enables efficient learning methods for linear kernels to be applied...
A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...