Exact expressions for double descent and implicit regularization via surrogate random design

10 December 2019

Papers citing "Exact expressions for double descent and implicit regularization via surrogate random design"

18 / 18 papers shown

Title
A Model Zoo on Phase Transitions in Neural Networks Konstantin Schurholt Léo Meynent Yefan Zhou Haiquan Lu Yaoqing Yang Damian Borth 68 0 0 25 Apr 2025
The Interpolating Information Criterion for Overparameterized Models Liam Hodgkinson Christopher van der Heide Roberto Salomone Fred Roosta Michael W. Mahoney 20 7 0 15 Jul 2023
High Dimensional Binary Classification under Label Shift: Phase Transition and Regularization Jiahui Cheng Minshuo Chen Hao Liu Tuo Zhao Wenjing Liao 36 0 0 01 Dec 2022
Sharp Analysis of Sketch-and-Project Methods via a Connection to Randomized Singular Value Decomposition Michal Derezinski E. Rebrova 27 16 0 20 Aug 2022
The Directional Bias Helps Stochastic Gradient Descent to Generalize in Kernel Regression Models Yiling Luo X. Huo Y. Mei 16 0 0 29 Apr 2022
Stochastic Perturbations of Tabular Features for Non-Deterministic Inference with Automunge Nicholas J. Teague AAML 13 1 0 18 Feb 2022
Model, sample, and epoch-wise descents: exact solution of gradient flow in the random feature model A. Bodin N. Macris 37 13 0 22 Oct 2021
A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning Yehuda Dar Vidya Muthukumar Richard G. Baraniuk 29 71 0 06 Sep 2021
Towards an Understanding of Benign Overfitting in Neural Networks Zhu Li Zhi-Hua Zhou A. Gretton MLT 33 35 0 06 Jun 2021
Provable Benefits of Overparameterization in Model Compression: From Double Descent to Pruning Neural Networks Xiangyu Chang Yingcong Li Samet Oymak Christos Thrampoulidis 35 50 0 16 Dec 2020
Sparse sketches with small inversion bias Michal Derezinski Zhenyu Liao Yan Sun Michael W. Mahoney 23 21 0 21 Nov 2020
Precise expressions for random projections: Low-rank approximation and randomized Newton Michal Derezinski Feynman T. Liang Zhenyu A. Liao Michael W. Mahoney 29 23 0 18 Jun 2020
An Overview of Neural Network Compression James OÑeill AI4CE 45 98 0 05 Jun 2020
Determinantal Point Processes in Randomized Numerical Linear Algebra Michal Derezinski Michael W. Mahoney 28 76 0 07 May 2020
Improved guarantees and a multiple-descent curve for Column Subset Selection and the Nyström method Michal Derezinski Rajiv Khanna Michael W. Mahoney 21 10 0 21 Feb 2020
Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning Charles H. Martin Michael W. Mahoney AI4CE 32 190 0 02 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 30 89 0 28 May 2018
Determinantal point processes for machine learning Alex Kulesza B. Taskar 162 1,123 0 25 Jul 2012