An integrated perspective of robustness in regression through the lens of the bias-variance trade-off
<|reference_start|>An integrated perspective of robustness in regression through the lens of the bias-variance trade-off: 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.<|reference_end|>
@article{okuno2024an,
    title={An integrated perspective of robustness in regression through the lens
  of the bias-variance trade-off},
    author={Akifumi Okuno},
    journal={arXiv preprint arXiv:2407.10418},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.10418},
    primaryClass={stat.ME cs.LG stat.ML}
}