In this paper, we address the tradeo between exploration and exploitation for agents which need to learn more about the structure of their environment in order to perform more e e...
Shlomo Argamon-Engelson, Sarit Kraus, Sigalit Sina
Abstract. In this paper we propose a novel approach to define task-driven regularization constraints in deformable image registration using learned deformation priors. Our method ...
Ben Glocker, Nikos Komodakis, Nassir Navab, Georgi...
Geometric constraint solving is a key issue in CAD/CAM. Since Owen’s seminal paper, solvers typically use graph based decomposition methods. However, these methods become diffi...
Abstract Computer vision is full of problems elegantly expressed in terms of energy minimization. We characterize a class of energies with hierarchical costs and propose a novel hi...
Andrew Delong, Lena Gorelick, Olga Veksler, Yuri B...
Abstract—We propose a novel search mechanism for unstructured p2p networks, and show that it is both scalable, i.e., it leads to a bounded query traffic load per peer as the pee...