Publications related to MATHICSE Technical Report : Multilevel weighted least squares polynomial approximation

What's the Frequency, Kenneth?: Sublinear Fourier Sampling Off the Grid

We design a sublinear Fourier sampling algorithm for a case of sparse off-grid frequency recovery. These are signals with the form ; i.e., exponential polynomials with a noise term. The frequencies satisfy and for some . We design a sublinear time randomiz ...

Springer Verlag2015

MATHICSE Technical Report : Discrete least squares polynomial approximation with random evaluations – application to parametric and stochastic elliptic PDES

Fabio Nobile, Giovanni Migliorati

Motivated by the numerical treatment of parametric and stochastic PDEs, we analyze the least-squares method for polynomial approximation of multivariate func- tions based on random sampling according to a given probability measure. Recent work has shown th ...

MATHICSE2014

Analysis of Discrete L2 Projection on Polynomial Spaces with Random Evaluations

Fabio Nobile, Giovanni Migliorati, Erik Gustaf Bogislaw Von Schwerin

We analyse the problem of approximating a multivariate function by discrete least-squares projection on a polynomial space starting from random, noise-free observations. An area of possible application of such technique is Uncertainty Quantification (UQ) f ...

2014

Calibration and field application of passive sampling for episodic exposure to polar organic pesticides in streams

Rainfall-triggered runoff is a major driver of pesticide input in streams. Only few studies have examined the suitability of passive sampling to quantify such episodic exposures. In this study, we used Empore(TM) styrene-divinylbenzene reverse phase sulfon ...

Elsevier2014

Approximation of Quantities of Interest in Stochastic PDEs by the Random Discrete $L^2$ Projection on Polynomial Spaces

Fabio Nobile, Giovanni Migliorati, Erik Gustaf Bogislaw Von Schwerin

In this work we consider the random discrete

L^2

projection on polynomial spaces (hereafter RDP) for the approximation of scalar quantities of interest (QOIs) related to the solution of a partial differential equation model with random input parameters. ...

Siam Publications2013

A preconditioned low-rank CG method for parameter-dependent Lyapunov matrix equations

Daniel Kressner, Christine Tobler

This paper is concerned with the numerical solution of symmetric large-scale Lyapunov equations with low-rank right-hand sides and coefficient matrices depending on a parameter. Specifically, we consider the situation when the parameter dependence is suffi ...

Wiley-Blackwell2013

High-throughput scanning electrochemical microscopy brushing of strongly tilted and curved surfaces

Hubert Girault, Andreas Stephan Lesch, Fernando Cortes Salazar, Dmitry Momotenko, Gunther Wittstock

The feasibility of high-throughput scanning electrochemical microscopy (SECM) of strongly tilted (tilt angles ≤4°) and curved substrates (diameter of curvature ≥9 cm) is demonstrated by brushing them with a soft linear array of carbon microelectrodes. This ...

Elsevier2013

Learning Ridge Functions With Randomized Sampling In High Dimensions

Volkan Cevher, Hemant Tyagi

We study the problem of learning ridge functions of the form f(x) = g(aT x), x ∈ ℝd, from random samples. Assuming g to be a twice continuously differentiable function, we leverage techniques from low rank matrix recovery literature to derive a uniform app ...

IEEE2012

MATHICSE Technical Report : Analysis of the discrete $L^2$ projection on polynomial spaces with random evaluations

Fabio Nobile, Giovanni Migliorati, Erik Gustaf Bogislaw Von Schwerin

We analyse the problem of approximating a multivariate function by discrete least-squares projection on a polynomial space starting from random, noise-free observations. An area of possible application of such technique is Uncertainty Quantification (UQ) f ...

MATHICSE2011

Distributed Sampling of Signals Linked by Sparse Filtering: Theory and Applications

Martin Vetterli, Olivier Roy, Yue Lu, Ali Hormati

We study the distributed sampling and centralized reconstruction of two correlated signals, modeled as the input and output of an unknown sparse filtering operation. This is akin to a Slepian-Wolf setup, but in the sampling rather than the lossless compres ...

2010

MATHICSE Technical Report : Multilevel weighted least squares polynomial approximation

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What's the Frequency, Kenneth?: Sublinear Fourier Sampling Off the Grid

MATHICSE Technical Report : Discrete least squares polynomial approximation with random evaluations – application to parametric and stochastic elliptic PDES

Analysis of Discrete L2 Projection on Polynomial Spaces with Random Evaluations

Calibration and field application of passive sampling for episodic exposure to polar organic pesticides in streams

Approximation of Quantities of Interest in Stochastic PDEs by the Random Discrete $L^2$ Projection on Polynomial Spaces

A preconditioned low-rank CG method for parameter-dependent Lyapunov matrix equations

High-throughput scanning electrochemical microscopy brushing of strongly tilted and curved surfaces

Learning Ridge Functions With Randomized Sampling In High Dimensions

MATHICSE Technical Report : Analysis of the discrete $L^2$ projection on polynomial spaces with random evaluations

Distributed Sampling of Signals Linked by Sparse Filtering: Theory and Applications

MATHICSE Technical Report : Discrete least squares polynomial approximation with random evaluations – application to parametric and stochastic elliptic PDES

Distributed Sampling of Signals Linked by Sparse Filtering: Theory and Applications

A preconditioned low-rank CG method for parameter-dependent Lyapunov matrix equations

High-throughput scanning electrochemical microscopy brushing of strongly tilted and curved surfaces

Analysis of Discrete L2 Projection on Polynomial Spaces with Random Evaluations

Calibration and field application of passive sampling for episodic exposure to polar organic pesticides in streams

Approximation of Quantities of Interest in Stochastic PDEs by the Random Discrete $L^2$ Projection on Polynomial Spaces

MATHICSE Technical Report : Analysis of the discrete $L^2$ projection on polynomial spaces with random evaluations

What's the Frequency, Kenneth?: Sublinear Fourier Sampling Off the Grid

Learning Ridge Functions With Randomized Sampling In High Dimensions