Probabilistic feature relevance learning (PFRL) is an effective technique for adaptively computing local feature relevance for content-based image retrieval. It however becomes le...
We study the problem of statistical model checking of probabilistic systems for PCTL unbounded until property P1p(ϕ1 U ϕ2) (where 1 ∈ {<, ≤, >, ≥}) using the computa...
Ru He, Paul Jennings, Samik Basu, Arka P. Ghosh, H...
Abstract. This text is an informal review of several randomized algorithms that have appeared over the past two decades and have proved instrumental in extracting efficiently quant...
This paper discusses how interval analysis can be used to solve a wide variety of problems in computer graphics. These problems include ray tracing, interference detection, polygo...
In this paper we present an algorithm for performance characterization of symbol localization systems. This algorithm is aimed to be a more “reliable” and “open” solution t...
Mathieu Delalandre, Jean-Yves Ramel, Ernest Valven...