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When a phenomenon is described by a parametric model and multiple datasets are available, a key problem in statistics is to discover which datasets are characterized by the same parameter values. Equivalently, one is interested in partitioning the family o ...
We introduce the reduced basis method (RBM) as an efficient tool for parametrized scattering problems in computational electromagnetics for problems where field solutions are computed using a standard Boundary Element Method (BEM) for the parametrized elec ...
Among emerging pollutants found in surface and ground waters, pharmaceuticals are currently receiving a particular interest. There are several physico/chemical parameters that could describe the fate of pharmaceuticals in the environment, so as their toxic ...
As the volumes of AI problems involving human knowledge are likely to soar, crowdsourcing has become essential in a wide range of world-wide-web applications. One of the biggest challenges of crowdsourcing is aggregating the answers collected from crowd wo ...
We consider the problem of actively learning \textit{multi-index} functions of the form f(x)=g(Ax)=∑i=1kgi(aiTx) from point evaluations of f. We assume that the function f is defined on an ℓ2-ball in \Reald, g is twice contin ...
Researchers and developers typically use I-V curves (current vs. potential) as a means to demonstrate good data fitting of a model under experimental validation. Despite the popularity of this method, assessment of the results can be intuitive rather than ...
Most hydrological models are valid at most only in a few places and cannot be reasonably transferred to other places or to far distant time periods. Transfer in space is difficult because the models are conditioned on past observations at particular places ...
A Dirichlet problem for orthogonal Hessians in two dimensions is explicitly solved, by characterizing all piecewise C-2 functions u Omega subset of R-2 -> R with orthogonal Hessian in terms of a property named "second order angle condition" as in (1 1) ...
Euclidean distance matrices (EDMs) are central players in many diverse fields including psychometrics, NMR spectroscopy, machine learning and sensor networks. However, they are not often exploited in signal processing. In this thesis, we analyze attributes ...
This paper focuses on urban environmental system identification. Wind-flow modeling is a challenging task because of simplifications of complex processes as well as geometry simplifications. Even a more detailed model may not be accurate because of uncerta ...
Institute of Electrical and Electronics Engineers ( IEEE )2013
