This paper studies a variational Bayesian unmixing algorithm for hyperspectral images based on the standard linear mixing model. Each pixel of the image is modeled as a linear com...
Olivier Eches, Nicolas Dobigeon, Jean-Yves Tourner...
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...
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...
Abstract—Detecting and localizing performance faults is crucial for operating large enterprise data centers. This problem is relatively straightforward to solve if each entity (a...
Vaishali P. Sadaphal, Maitreya Natu, Harrick M. Vi...
—We study scalable routing for a sensor network deployed in complicated 3D settings such as underground tunnels in gas system or water system. The nodes are in general 3D space b...
Xiaokang Yu, Xiaotian Yin, Wei Han, Jie Gao, Xianf...