Data for: Benefits of noise in M-estimators: Optimal noise level and probability density

Published: 23 Oct 2019 | Version 1 | DOI: 10.17632/h2nxrghrfw.1
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Description of this data

This zipped file contains the program of solving the inequality constrained optimization problem of Eq.(A.6) by the interior point function methods (Matlab code).

Experiment data files

This data is associated with the following publication:

Benefits of noise in M-estimators: Optimal noise level and probability density

Published in: Physica A: Statistical Mechanics and its Applications

Latest version

  • Version 1

    2019-10-23

    Published: 2019-10-23

    DOI: 10.17632/h2nxrghrfw.1

    Cite this dataset

    Duan, Fabing (2019), “Data for: Benefits of noise in M-estimators: Optimal noise level and probability density”, Mendeley Data, v1 http://dx.doi.org/10.17632/h2nxrghrfw.1

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Categories

Constrained Optimization

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The files associated with this dataset are licensed under a Public Domain Dedication licence.

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