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We study the risk of minimum-norm interpolants of data in Reproducing Kernel Hilbert Spaces.
Optimal rates for the regularized least-squares algorithm
Andrea Caponnetto and Ernesto De Vito · 2007
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Learning without concentration
Shahar Mendelson · 2014
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Bounding the smallest singular value of a random matrix without concentration
Vladimir Koltchinskii and Shahar Mendelson · 2015
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Empirical entropy, minimax regret and minimax risk
Alexander Rakhlin, Karthik Sridharan, and Alexandre B. Tsybakov · 2017
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Gradient descent provably optimizes over-parameterized neural networks
Simon S Du, Xiyu Zhai, Barnabas Poczos, and Aarti Singh · 2018
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Neural tangent kernel: Convergence and generalization in neural networks
Arthur Jacot, Franck Gabriel, and Clément Hongler · 2018
Cited alongside, same era.
Just interpolate: Kernel” ridgeless” regression can generalize
Tengyuan Liang and Alexander Rakhlin · 2018
Cited alongside, same era.
Consistency of interpolation with laplace kernels is a high-dimensional phenomenon
Alexander Rakhlin and Xiyu Zhai · 2018
Cited alongside, same era.
Benign overfitting in linear regression
Peter L Bartlett, Philip M Long, Gábor Lugosi, and Alexander Tsigler · 2019
Cited alongside, same era.
Reconciling modern machine learning and the bias-variance trade-off
Mikhail Belkin, Daniel Hsu, Siyuan Ma, and Soumik Mandal
Cited in the paper.
Overfitting or perfect fitting? risk bounds for classification and regression rules that interpolate
Mikhail Belkin, Daniel Hsu, and Partha Mitra
Cited in the paper.
To understand deep learning we need to understand kernel learning
Mikhail Belkin, Siyuan Ma, and Soumik Mandal
Cited in the paper.
Does data interpolation contradict statistical optimality?
Mikhail Belkin, Alexander Rakhlin, and Alexandre B Tsybakov
Cited in the paper.
Does learning require memorization? a short tale about a long tail
Vitaly Feldman · 2019
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Linearized two-layers neural networks in high dimension
Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, and Andrea Montanari · 2019
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Surprises in high-dimensional ridgeless least squares interpolation
Trevor Hastie, Andrea Montanari, Saharon Rosset, and Ryan J Tibshirani · 2019
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The generalization error of random features regression: Precise asymptotics and double descent curve
Song Mei and Andrea Montanari · 2019
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