We propose a fully Bayesian approach for generalized kernel models (GKMs), which are extensions of generalized linear models in the feature space induced by a reproducing kernel. ...
Zhihua Zhang, Guang Dai, Donghui Wang, Michael I. ...
We generalize the model theory of small profinite structures developed by Newelski to the case of compact metric spaces considered together with compact groups of homeomorphisms a...
This paper is devoted to the study of some qualitative and quantitative aspects of nonlinear propagation phenomena in diffusive media. More precisely, we consider the case a react...
Abstract--Reconstruction algorithms for fluorescence tomography have to address two crucial issues : (i) the ill-posedness of the reconstruction problem, (ii) the large scale of nu...
The generalized Gaussian distribution (GGD) provides a flexible and suitable tool for data modeling and simulation, however the characterization of the complex-valued GGD, in parti...