Correcting Data Corruption Errors for Multivariate Function Approximation-Reference-Cited by-同舟云学术

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Correcting Data Corruption Errors for Multivariate Function Approximation

Published:2016-01 Issue:4 Volume:38 Page:A2492-A2511
ISSN:1064-8275
Container-title:SIAM Journal on Scientific Computing
language:en
Short-container-title:SIAM J. Sci. Comput.

Author:

Shin Yeonjong,Xiu Dongbin

Funder

Air Force Office of Scientific Research

Defense Advanced Research Projects Agency

Division of Mathematical Sciences

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Subject

Applied Mathematics,Computational Mathematics

Link

http://epubs.siam.org/doi/pdf/10.1137/16M1059473

Reference18 articles.

1. On the discrete linear L1 approximation and L1 solutions of overdetermined linear equations

2. An Improved Algorithm for Discrete $l_1 $ Linear Approximation

3. Asymptotic Theory of Least Absolute Error Regression

4. Least Absolute Deviations Curve-Fitting

5. Minimum ℓ1, ℓ2, and ℓ∞ Norm Approximate Solutions to an Overdetermined System of Linear Equations

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1. Towards Optimal Sampling for Learning Sparse Approximations in High Dimensions;High-Dimensional Optimization and Probability;2022

2. Identification of Corrupted Data via $k$-Means Clustering for Function Approximation;CSIAM Transactions on Applied Mathematics;2021-06

3. Error Localization of Best $L_{1}$ Polynomial Approximants;SIAM Journal on Numerical Analysis;2021-01

4. Level set methods for stochastic discontinuity detection in nonlinear problems;Journal of Computational Physics;2019-09

5. Correcting for unknown errors in sparse high-dimensional function approximation;Numerische Mathematik;2019-05-15

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