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1903.07571
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Two models of double descent for weak features
SIAM Journal on Mathematics of Data Science (SIMODS), 2019
18 March 2019
M. Belkin
Daniel J. Hsu
Ji Xu
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Papers citing
"Two models of double descent for weak features"
19 / 269 papers shown
Finite Depth and Width Corrections to the Neural Tangent Kernel
International Conference on Learning Representations (ICLR), 2019
Boris Hanin
Mihai Nica
MDE
206
162
0
13 Sep 2019
Theoretical Issues in Deep Networks: Approximation, Optimization and Generalization
Proceedings of the National Academy of Sciences of the United States of America (PNAS), 2019
T. Poggio
Andrzej Banburski
Q. Liao
ODL
196
185
0
25 Aug 2019
The generalization error of random features regression: Precise asymptotics and double descent curve
Communications on Pure and Applied Mathematics (CPAM), 2019
Song Mei
Andrea Montanari
513
675
0
14 Aug 2019
Benign Overfitting in Linear Regression
Proceedings of the National Academy of Sciences of the United States of America (PNAS), 2019
Peter L. Bartlett
Philip M. Long
Gábor Lugosi
Alexander Tsigler
MLT
405
853
0
26 Jun 2019
Generalization Guarantees for Neural Networks via Harnessing the Low-rank Structure of the Jacobian
Samet Oymak
Zalan Fabian
Mingchen Li
Mahdi Soltanolkotabi
MLT
229
100
0
12 Jun 2019
Does Learning Require Memorization? A Short Tale about a Long Tail
Symposium on the Theory of Computing (STOC), 2019
Vitaly Feldman
TDI
539
581
0
12 Jun 2019
On the number of variables to use in principal component regression
Neural Information Processing Systems (NeurIPS), 2019
Ji Xu
Daniel J. Hsu
173
5
0
04 Jun 2019
MaxiMin Active Learning in Overparameterized Model Classes}
IEEE Journal on Selected Areas in Information Theory (JSAIT), 2019
Mina Karzand
Robert D. Nowak
159
21
0
29 May 2019
Implicit Rugosity Regularization via Data Augmentation
Daniel LeJeune
Randall Balestriero
Hamid Javadi
Richard G. Baraniuk
210
4
0
28 May 2019
Empirical Risk Minimization in the Interpolating Regime with Application to Neural Network Learning
Machine-mediated learning (ML), 2019
Nicole Mücke
Ingo Steinwart
AI4CE
185
2
0
25 May 2019
Linearized two-layers neural networks in high dimension
Annals of Statistics (Ann. Stat.), 2019
Behrooz Ghorbani
Song Mei
Theodor Misiakiewicz
Andrea Montanari
MLT
278
258
0
27 Apr 2019
Surprises in High-Dimensional Ridgeless Least Squares Interpolation
Annals of Statistics (Ann. Stat.), 2019
Trevor Hastie
Andrea Montanari
Saharon Rosset
Robert Tibshirani
875
819
0
19 Mar 2019
Consistent Risk Estimation in Moderately High-Dimensional Linear Regression
Ji Xu
A. Maleki
Kamiar Rahnama Rad
Daniel J. Hsu
360
13
0
05 Feb 2019
Scaling description of generalization with number of parameters in deep learning
Mario Geiger
Arthur Jacot
S. Spigler
Franck Gabriel
Levent Sagun
Stéphane dÁscoli
Giulio Biroli
Clément Hongler
Matthieu Wyart
332
204
0
06 Jan 2019
Regularized Zero-Variance Control Variates
Leah F. South
Chris J. Oates
Antonietta Mira
Christopher C. Drovandi
BDL
574
21
0
13 Nov 2018
A jamming transition from under- to over-parametrization affects loss landscape and generalization
S. Spigler
Mario Geiger
Stéphane dÁscoli
Levent Sagun
Giulio Biroli
Matthieu Wyart
377
160
0
22 Oct 2018
A Modern Take on the Bias-Variance Tradeoff in Neural Networks
Brady Neal
Sarthak Mittal
A. Baratin
Vinayak Tantia
Matthew Scicluna
Damien Scieur
Alexia Jolicoeur-Martineau
251
178
0
19 Oct 2018
Optimal ridge penalty for real-world high-dimensional data can be zero or negative due to the implicit ridge regularization
D. Kobak
Jonathan Lomond
Benoit Sanchez
218
96
0
28 May 2018
High-dimensional dynamics of generalization error in neural networks
Madhu S. Advani
Andrew M. Saxe
AI4CE
277
503
0
10 Oct 2017
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