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

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Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Fabio Nobile, Giovanni Migliorati

We analyze the accuracy of the discrete least-squares approximation of a function

u

in multivariate polynomial spaces

P_\Lambda:=span\{y\mapsto y^\nu \,: \, \nu\in \Lambda\}

with

\Lambda\subset N_0^d

over the domain

\Gamma:=[-1,1]^d

, based on the s ...

2017

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

Graph Chatbot

Chattez avec Graph Search

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Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

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Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression

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Reconstruction of 3D scattered data via radial basis functions by efficient and robust techniques

MATHICSE Technical Report : Multilevel weighted least squares polynomial approximation

Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression

Smoothing Alternating Direction Methods for Fully Nonsmooth Constrained Convex Optimization

Case Study of Data Assimilation Methods with the LWR-Proteus Phase II Experimental Campaign

Optimal Rates for Spectral Algorithms with Least-Squares Regression over Hilbert Spaces

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension