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With noisy and asynchronous high-frequency data collected for an ultra-large number of assets, we estimate high-dimensional spot volatility matrices satisfying a low-rank plus sparse structure. A loca...
Sparse constraints on signal decompositions are justified bytypical sensor data used in a variety of signal processing fields such as acoustics, medical imaging, or wireless, but moreover can lead to ...
We describe a magneto-gradiometric survey performed in the «Mar Piccolo» of Taranto, Italy in May 2005 for environmental purposes. This region, which is a noisy harbour environment, provides...
Given a matrix M of low-rank, we consider the problem of reconstructing it from noisy observations of a small, random subset of its entries. The problem arises in a variety of applications, from colla...
We consider the problem of positioning a cloud of points in the Euclidean space R d, using noisy measurements of a subset of pairwise distances. This task has applications in various areas, such as se...
Rolling array pattern broad band magnetotelluric (MT) data was acquired in the Koyna-Warna (Maharashtra, India) seismic zone during 2012-14 field campaigns. The main objective of this study is to id...
Rolling array pattern broad band magnetotelluric (MT) data was acquired in the Koyna-Warna (Maharashtra, India) seismic zone during 2012-14 field campaigns. The main objective of this study is to iden...
We have described a method of obtaining useful information from noisy seismic refraction data. The simple method, tagged beam-forming technique, is based on the basic time-distance equations of refrac...
Many models for sparse regression typically assume that the covariates are known completely, and without noise. Particularly in high-dimensional applications, this is often not the case. This paper de...
Abstract: In this paper, we introduce a sparse approximation property of order $s$ for a measurement matrix ${\bf A}$: $$\|{\bf x}_s\|_2\le D \|{\bf A}{\bf x}\|_2+ \beta \frac{\sigma_s({\bf x})}{\sqrt...
Abstract: We consider the problem of detecting a small subset of defective items from a large set via non-adaptive "random pooling" group tests. We consider both the case when the measurements are noi...
Abstract: We study the dynamics of the large N limit of the Kuramoto model of coupled phase oscillators, subject to white noise. We introduce the notion of shadow inertial manifold and we prove their ...
Abstract: The sensitivity in optical interferometry is strongly affected by losses during the signal propagation or at the detection stage. The optimal quantum states of the probing signals in the pre...
Abstract: In the present paper we consider Laplace deconvolution on the basis of discrete noisy data observed on the interval which length may increase with a sample size. Although this problem arises...
We derive a method to reconstruct Gaussian signals from linear measurements with Gaussian noise. This new algorithm is intended for applications in astrophysics and other sciences. The starting point ...

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