Inference in Markov Decision Processes has recently received interest as a means to infer goals of an observed action, policy recognition, and also as a tool to compute policies. ...
This paper deals with denoising of density images with bad Poisson statistics (low count rates), where the reconstruction of the major structures seems the only reasonable task. Ob...
In this paper, we develop a novel online algorithm based on the Sequential Monte Carlo (SMC) samplers framework for posterior inference in Dirichlet Process Mixtures (DPM) (DelMor...
Abstract— Correct and efficient estimation of the Hurst parameter of long-range dependent (LRD) video traces is important in traffic analysis. The low computational cost and th...
Nikola Cackov, Zelimir Lucic, Momcilo Bogdanov, Lj...
Abstract. We propose a new solution approach for the Job Shop Problem with Sequence Dependent Setup Times (SDST-JSP). The problem consists in scheduling jobs, each job being a set ...
Christian Artigues, Sana Belmokhtar, Dominique Fei...