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An integrated perspective of robustness in regression through the lens of the bias-variance trade-off

2024-07-15Code Available0· sign in to hype

Akifumi Okuno

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Abstract

This paper presents an integrated perspective on robustness in regression. Specifically, we examine the relationship between traditional outlier-resistant robust estimation and robust optimization, which focuses on parameter estimation resistant to imaginary dataset-perturbations. While both are commonly regarded as robust methods, these concepts demonstrate a bias-variance trade-off, indicating that they follow roughly converse strategies.

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