Most machine learning algorithms share the following drawback: they only output bare predictions but not the con dence in those predictions. In the 1960s algorithmic information t...
This paper deals with the problem of time-resolved fluorescence diffuse optical tomography. We propose a new reconstruction scheme based on a multi-resolution approximation of th...
Nicolas Ducros, Anabela da Silva, Jean-Marc Dinten...
— We consider the problem of designing controllers for spatially-varying interconnected systems distributed in one spatial dimension. The matrix structure of such systems can be ...
We discuss two approximation approaches, the primal-dual schema and the local-ratio technique. We present two relatively simple frameworks, one for each approach, which extend know...
Abstract. We consider the problem of accurately estimating the number of approximate XML answers for a given query, and propose an efficient method that (1) accurately computes sel...