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High-Dimensional Asymptotics of Prediction: Ridge Regression and Classification

10 July 2015

Papers citing "High-Dimensional Asymptotics of Prediction: Ridge Regression and Classification"

32 / 82 papers shown

Title
Out-of-sample error estimate for robust M-estimators with convex penalty Pierre C. Bellec 129 17 0 26 Aug 2020
Revisiting minimum description length complexity in overparameterized models Raaz Dwivedi Chandan Singh Bin Yu Martin J. Wainwright 72 5 0 17 Jun 2020
Kernel Alignment Risk Estimator: Risk Prediction from Training Data Arthur Jacot Berfin cSimcsek Francesco Spadaro Clément Hongler Franck Gabriel 80 68 0 17 Jun 2020
Fundamental Limits of Ridge-Regularized Empirical Risk Minimization in High Dimensions Hossein Taheri Ramtin Pedarsani Christos Thrampoulidis 84 29 0 16 Jun 2020
Asymptotics of Ridge (less) Regression under General Source Condition Dominic Richards Jaouad Mourtada Lorenzo Rosasco 88 73 0 11 Jun 2020
$On the Optimal Weighted $\ell_2$ Regularization in Overparameterized Linear Regression$ On the Optimal Weighted $\ell_2$ Regularization in Overparameterized Linear Regression Denny Wu Ji Xu 75 123 0 10 Jun 2020
A Random Matrix Analysis of Random Fourier Features: Beyond the Gaussian Kernel, a Precise Phase Transition, and the Corresponding Double Descent Zhenyu Liao Romain Couillet Michael W. Mahoney 91 93 0 09 Jun 2020
Spectra of the Conjugate Kernel and Neural Tangent Kernel for linear-width neural networks Z. Fan Zhichao Wang 115 74 0 25 May 2020
Fast cross-validation for multi-penalty ridge regression M. A. van de Wiel M. V. Nee A. Rauschenberger 34 3 0 19 May 2020
Finite-sample Analysis of Interpolating Linear Classifiers in the Overparameterized Regime Niladri S. Chatterji Philip M. Long 95 109 0 25 Apr 2020
Regularization in High-Dimensional Regression and Classification via Random Matrix Theory Panagiotis Lolas 84 14 0 30 Mar 2020
Rethinking Parameter Counting in Deep Models: Effective Dimensionality Revisited Wesley J. Maddox Gregory W. Benton A. Wilson 136 61 0 04 Mar 2020
Optimal Regularization Can Mitigate Double Descent Preetum Nakkiran Prayaag Venkat Sham Kakade Tengyu Ma 85 133 0 04 Mar 2020
The role of regularization in classification of high-dimensional noisy Gaussian mixture Francesca Mignacco Florent Krzakala Yue M. Lu Lenka Zdeborová 58 90 0 26 Feb 2020
Implicit Regularization of Random Feature Models Arthur Jacot Berfin Simsek Francesco Spadaro Clément Hongler Franck Gabriel 85 83 0 19 Feb 2020
Exact expressions for double descent and implicit regularization via surrogate random design Michal Derezinski Feynman T. Liang Michael W. Mahoney 82 78 0 10 Dec 2019
The Implicit Regularization of Ordinary Least Squares Ensembles Daniel LeJeune Hamid Javadi Richard G. Baraniuk 143 43 0 10 Oct 2019
Ridge Regression: Structure, Cross-Validation, and Sketching Sifan Liu Yan Sun CML 115 48 0 06 Oct 2019
Asymptotic Bayes risk for Gaussian mixture in a semi-supervised setting Marc Lelarge Léo Miolane 71 29 0 08 Jul 2019
WONDER: Weighted one-shot distributed ridge regression in high dimensions Yan Sun Yueqi Sheng OffRL 92 51 0 22 Mar 2019
Surprises in High-Dimensional Ridgeless Least Squares Interpolation Trevor Hastie Andrea Montanari Saharon Rosset Robert Tibshirani 305 747 0 19 Mar 2019
A Continuous-Time View of Early Stopping for Least Squares Alnur Ali J. Zico Kolter Robert Tibshirani 104 97 0 23 Oct 2018
Optimal Covariance Estimation for Condition Number Loss in the Spiked Model D. Donoho Behrooz Ghorbani 141 7 0 17 Oct 2018
Asymptotics for Sketching in Least Squares Regression Yan Sun Sifan Liu 61 13 0 14 Oct 2018
Adapting to Unknown Noise Distribution in Matrix Denoising Andrea Montanari Feng Ruan Jun Yan 100 13 0 06 Oct 2018
Distributed linear regression by averaging Yan Sun Yueqi Sheng FedML 94 66 0 30 Sep 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 94 89 0 28 May 2018
On the dimension effect of regularized linear discriminant analysis Cheng-Long Wang Binyan Jiang 51 15 0 09 Oct 2017
Permutation methods for factor analysis and PCA Yan Sun 82 54 0 02 Oct 2017
Optimal prediction in the linearly transformed spiked model Edgar Dobriban W. Leeb A. Singer 83 20 0 07 Sep 2017
High-dimensional regression adjustments in randomized experiments Stefan Wager Wenfei Du Jonathan E. Taylor Robert Tibshirani 299 117 0 22 Jul 2016
Prediction risk for the horseshoe regression A. Bhadra J. Datta Yunfan Li Nicholas G. Polson Brandon T. Willard 173 16 0 16 May 2016