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18 Μαρ 2019 · The "double descent" risk curve was proposed to qualitatively describe the out-of-sample prediction accuracy of variably-parameterized machine learning models. This article provides a precise mathematical analysis for the shape of this curve in two simple data models with the least squares/least norm predictor.
The \double descent" risk curve was proposed by Belkin, Hsu, Ma, and Mandal [Bel+19] as a general way to qualitatively describe the out-of-sample prediction performance of variably-parameterized machine learning models. This risk curve reconciles the classical bias-variance trade-o with the behavior of predictive models
The “double descent” risk curve was proposed to qualitatively describe the out-of-sample prediction accuracy of variably parameterized machine learning models. This article provides a precise mathematical analysis for the shape of this curve in two simple data models with the least squares/least norm predictor.
18 Μαρ 2019 · This paper presents a VC-theoretical analysis of double descent and shows that it can be fully explained by classical VC-generalization bounds, and illustrates an application of analytic VC-bounds for modeling double descent for classification, using empirical results for several learning methods.
In this article, we show that key aspects of the “double descent” risk curve can be observed with the least squares/least norm predictor in two simple random features models. The first is a Gaussian model studied by Breiman and Freedman [7] in the classical p n regime, while the second is a Fourier series model for functions on the circle.
14 Δεκ 2020 · As a first step of understanding this mystery, the "benign overfitting" or "double-descent" phenomenon 2 has been discovered and studied for overfitted solutions of single-task linear...
The "double descent" risk curve was proposed to qualitatively describe the out-of-sample prediction accuracy of variably-parameterized machine learning models. This article provides a precise mathematical analysis for the shape of this curve in two simple data models with the least squares/least norm predictor.
