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Testing mutual independence among several random vectors of arbitrary dimensions is a challenging problem in Statistics, and it has gained considerable interest in recent years. In this article, we propose some nonparametric tests based on different notion ...
The increasing availability of network data is leading to a growing interest in processing of signals on graphs. One notable tool for extending conventional signal-processing operations to networks is the graph Fourier transform that can be obtained as the ...
Institute of Electrical and Electronics Engineers2016
Nowadays, the global increase of energy demand and the necessity to satisfy high safety standards have led engineers and scientists to focus their efforts in order to understand and describe fundamental phenomena that are crucial for a correct design of th ...
The performance of many color science and imaging algorithms are evaluated based on their mean errors. However, if these errors are not normally distributed, statistical evaluations based on the mean are not appropriate performance metrics. We present a no ...
Parametric option pricing models are largely used in Finance. These models capture several features of asset price dynamics. However, their pricing performance can be significantly enhanced when they are combined with nonparametric learning approaches that ...
In the last decade, several Life Cycle Assessment (LCA) methods for assessing impact of products on living resources have been developed. Beyond the quantified assessments of impacts on living systems, it also checked the feasibility of the impact assessme ...
Tomographic reconstruction from positron emission tomography (PET) data is an ill-posed problem that requires regularization. An attractive approach is to impose an ℓ1 -regularization constraint, which favors sparse solutions in the wavelet dom ...
Institute of Electrical and Electronics Engineers2008
The framework of graphical models is a cornerstone of applied Statistics, allowing for an intuitive graphical specification of the main features of a model, and providing a basis for general Bayesian inference computations though belief propagation (BP). I ...
