Nonparametric methods are widely applicable to statistical learning problems, since they rely on a few modeling assumptions. In this context, the fresh look advocated here permeat...
In the important domain of array shape calibration, the near-field case poses a challenging problem due to the array response complexity induced by the range effect. In this pape...
This paper describes a new approximate maximum-likelihood (ML) MIMO detection approach by studying a Lagrangian dual relaxation (LDR) of ML. Unlike many existing relaxed ML method...
This paper investigates a Bayesian model and a Markov chain Monte Carlo (MCMC) algorithm for gene factor analysis. Each sample in the dataset is decomposed as a linear combination...
Cecile Bazot, Nicolas Dobigeon, Jean-Yves Tournere...
—In this work we develop a distributed boundary detection algorithm, dubbed Coconut, for 3D wireless sensor networks. It first constructs a tetrahedral structure to delineate th...