Best Choices for Regularization Parameters in Learning Theory: On the Bias-Variance Problem

Felipe Cucker; Steve Smale

doi:10.1007/s102080010030

Best Choices for Regularization Parameters in Learning Theory: On the Bias-Variance Problem

Felipe Cucker, Steve Smale

Department of Mathematics

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

222 Citations (Scopus)

Original language	English
Pages (from-to)	413-428
Journal	Foundations of Computational Mathematics
Volume	2
Issue number	4
DOIs	https://doi.org/10.1007/s102080010030
Publication status	Published - Nov 2002

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title = "Best Choices for Regularization Parameters in Learning Theory: On the Bias-Variance Problem",

author = "Felipe Cucker and Steve Smale",

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JO - Foundations of Computational Mathematics

JF - Foundations of Computational Mathematics

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Best Choices for Regularization Parameters in Learning Theory: On the Bias-Variance Problem

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