The purpose of this paper is twofold. An immediate practical use of the presented algorithm is its applicability to the parametric solution of underdetermined linear ordinary diļ¬...
We investigate the eļ¬cient iterative solution of large-scale sparse linear systems on shared-memory multiprocessors. Our parallel approach is based on a multilevel ILU precondit...
In the last decade, cluster computing has become the most popular high-performance computing architecture. Although numerous technological innovations have been proposed to improv...
This paper addresses the problem of minimizing the average running time of the Las Vegas type algorithm, both in serial and parallel setups. The necessary conditions for the exist...
Oleg V. Shylo, Timothy Middelkoop, Panos M. Pardal...
āIn this paper, we introduce a novel method to solve shape alignment problems. We use gray-scale āimagesā to represent source shapes, and propose a novel two-component Gaussi...
āIn solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. The resulting ...
āInferring latent structures from observations helps to model and possibly also understand underlying data generating processes. A rich class of latent structures are the latent ...
āWe propose a convex formulation for silhouette and stereo fusion in 3D reconstruction from multiple images. The key idea is to show that the reconstruction problem can be cast a...
This paper proposes a general method for improving image descriptors using discriminant projections. Two methods based on Linear Discriminant Analysis have been recently introduce...
āThis paper addresses the issue of matching rigid and articulated shapes through probabilistic point registration. The problem is recast into a missing data framework where unkno...
Radu Horaud, Florence Forbes, Manuel Yguel, Guilla...