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Magnetic resonance imaging (MRI) is highly susceptible to subject's motion and can significantly degrade image quality. In brain MRI exams, involuntary head movements can affect the sampled k-space data. Such unintended alterations may result in visible im ...
This paper presents a non-asymptotic upper bound for the estimation error of the constrained lasso, under the high-dimensional (n≪p) setting. In contrast to existing results, the error bound in this paper is sharp, is valid when the parameter to be e ...
As radio telescope data is now increasingly high-dimensional, data reduction has become essential to reduce computational load while preserving accurate signal reconstruction. Gridding the continuous Fourier visibilities represents the standard approach to ...
We propose a novel Bayesian approach to automated delineation of curvilinear structures that form complex and potentially loopy networks. By representing the image data as a graph of potential paths, we first show how to weight these paths using discrimina ...
Institute of Electrical and Electronics Engineers2016
n this paper, we provide an extension of the scalable algorithm proposed in (Riverso et al., 2015) for the design of Plug-and-Play (PnP) controllers for AC Islanded microGrids (ImGs). The method in (Riverso et al., 2015) assumes DGUs are arranged in a load ...
Schizophrenia research has focused on single mechanisms mainly. Classically, a paradigm is chosen, such as a cognitive or perceptual test. The outcome is usually that schizophrenia patients perform worse than controls. Substantial research is then spent to ...
The recently discovered unique optoelectronic properties and chemical robustness of mono- or few-layer two-dimensional (2D) semiconducting transition metal dichalcogenides (TMDs) such as MoS2, WS2, MoSe2, and WSe2 have opened new possibilities for solar en ...
We compute the motivic Donaldson-Thomas invariants of the one-loop quiver, with an arbitrary potential. This is the first computation of motivic Donaldson-Thomas invariants to use in an essential way the full machinery of (mu) over cap -equivariant motives ...
In this paper, we propose a novel algorithm for dimensionality reduction that uses as a criterion the mutual information (MI) between the transformed data and their cor- responding class labels. The MI is a powerful criterion that can be used as a proxy to ...
Institute of Electrical and Electronics Engineers2015
We are interested in the large-scale learning of Mahalanobis distances, with a particular focus on person re-identification. We propose a metric learning formulation called Weighted Approximate Rank Component Analysis (WARCA). WARCA optimizes the precision ...