Cargando…
A Robust Learning Approach for Regression Models Based on Distributionally Robust Optimization
We present a Distributionally Robust Optimization (DRO) approach to estimate a robustified regression plane in a linear regression setting, when the observed samples are potentially contaminated with adversarially corrupted outliers. Our approach mitigates the impact of outliers by hedging against a...
Autores principales: | Chen, Ruidi, Paschalidis, Ioannis Ch. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8378760/ https://www.ncbi.nlm.nih.gov/pubmed/34421397 |
Ejemplares similares
-
Distributionally robust learning-to-rank under the Wasserstein metric
por: Sotudian, Shahabeddin, et al.
Publicado: (2023) -
Robust Asynchronous Stochastic Gradient-Push: Asymptotically Optimal and Network-Independent Performance for Strongly Convex Functions
por: Spiridonoff, Artin, et al.
Publicado: (2020) -
Detection of unwarranted CT radiation exposure from patient and imaging protocol meta-data using regularized regression
por: Chen, Ruidi, et al.
Publicado: (2019) -
Robust Bayesian Regression with Synthetic Posterior Distributions
por: Hashimoto, Shintaro, et al.
Publicado: (2020) -
Robust regression and model compression
por: Ivanov, Marian
Publicado: (2018)