Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
1912.04533
Cited By
v1
v2
v3 (latest)
Exact expressions for double descent and implicit regularization via surrogate random design
Neural Information Processing Systems (NeurIPS), 2019
10 December 2019
Michal Derezinski
Feynman T. Liang
Michael W. Mahoney
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Exact expressions for double descent and implicit regularization via surrogate random design"
50 / 61 papers shown
Matricial Free Energy as a Gaussianizing Regularizer: Enhancing Autoencoders for Gaussian Code Generation
Rishi Sonthalia
Raj Rao Nadakuditi
101
0
0
20 Oct 2025
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias
Yuanzhe Hu
Kinshuk Goel
Vlad Killiakov
Yaoqing Yang
310
3
0
06 Jun 2025
A Model Zoo on Phase Transitions in Neural Networks
Konstantin Schurholt
Léo Meynent
Yefan Zhou
Haiquan Lu
Yaoqing Yang
Damian Borth
367
2
0
25 Apr 2025
Double Descent Meets Out-of-Distribution Detection: Theoretical Insights and Empirical Analysis on the role of model complexity
Mouin Ben Ammar
David Brellmann
Arturo Mendoza
Antoine Manzanera
Gianni Franchi
OODD
395
0
0
04 Nov 2024
Generalization for Least Squares Regression With Simple Spiked Covariances
Jiping Li
Rishi Sonthalia
222
1
0
17 Oct 2024
Recent and Upcoming Developments in Randomized Numerical Linear Algebra for Machine Learning
Michał Dereziński
Michael W. Mahoney
277
18
0
17 Jun 2024
Near-Interpolators: Rapid Norm Growth and the Trade-Off between Interpolation and Generalization
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Yutong Wang
Rishi Sonthalia
Wei Hu
292
7
0
12 Mar 2024
"Lossless" Compression of Deep Neural Networks: A High-dimensional Neural Tangent Kernel Approach
Lingyu Gu
Yongqiang Du
Yuan Zhang
Di Xie
Shiliang Pu
Robert C. Qiu
Zhenyu Liao
236
9
0
01 Mar 2024
A PAC-Bayesian Perspective on the Interpolating Information Criterion
Liam Hodgkinson
Christopher van der Heide
Roberto Salomone
Fred Roosta
Michael W. Mahoney
275
2
0
13 Nov 2023
On High-Dimensional Asymptotic Properties of Model Averaging Estimators
Ryo Ando
F. Komaki
MoMe
108
6
0
18 Aug 2023
Does Double Descent Occur in Self-Supervised Learning?
A. Lupidi
Yonatan Gideoni
Dulhan Jayalath
SSL
145
3
0
15 Jul 2023
The Interpolating Information Criterion for Overparameterized Models
Liam Hodgkinson
Christopher van der Heide
Roberto Salomone
Fred Roosta
Michael W. Mahoney
239
10
0
15 Jul 2023
Least Squares Regression Can Exhibit Under-Parameterized Double Descent
Neural Information Processing Systems (NeurIPS), 2023
Xinyue Li
Rishi Sonthalia
323
5
0
24 May 2023
High Dimensional Binary Classification under Label Shift: Phase Transition and Regularization
Sampling Theory, Signal Processing, and Data Analysis (SampTA), 2022
Jiahui Cheng
Minshuo Chen
Hao Liu
Tuo Zhao
Wenjing Liao
314
1
0
01 Dec 2022
Asymptotics of the Sketched Pseudoinverse
SIAM Journal on Mathematics of Data Science (SIMODS), 2022
Daniel LeJeune
Pratik V. Patil
Hamid Javadi
Richard G. Baraniuk
Robert Tibshirani
200
11
0
07 Nov 2022
Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes
International Conference on Machine Learning (ICML), 2022
Liam Hodgkinson
Christopher van der Heide
Fred Roosta
Michael W. Mahoney
UQCV
256
7
0
14 Oct 2022
Sharp Analysis of Sketch-and-Project Methods via a Connection to Randomized Singular Value Decomposition
SIAM Journal on Mathematics of Data Science (SIMODS), 2022
Michal Derezinski
E. Rebrova
269
24
0
20 Aug 2022
Investigating the Impact of Model Width and Density on Generalization in Presence of Label Noise
Conference on Uncertainty in Artificial Intelligence (UAI), 2022
Yihao Xue
Kyle Whitecross
Baharan Mirzasoleiman
NoLa
376
2
0
17 Aug 2022
Implicit Regularization or Implicit Conditioning? Exact Risk Trajectories of SGD in High Dimensions
Neural Information Processing Systems (NeurIPS), 2022
Courtney Paquette
Elliot Paquette
Ben Adlam
Jeffrey Pennington
137
19
0
15 Jun 2022
Hardness of Maximum Likelihood Learning of DPPs
Annual Conference Computational Learning Theory (COLT), 2022
Elena Grigorescu
Brendan Juba
K. Wimmer
Ning Xie
159
6
0
24 May 2022
The Directional Bias Helps Stochastic Gradient Descent to Generalize in Kernel Regression Models
International Symposium on Information Theory (ISIT), 2022
Yiling Luo
X. Huo
Y. Mei
207
0
0
29 Apr 2022
Implicit Regularization Properties of Variance Reduced Stochastic Mirror Descent
International Symposium on Information Theory (ISIT), 2022
Yiling Luo
X. Huo
Y. Mei
162
5
0
29 Apr 2022
Bias-variance decomposition of overparameterized regression with random linear features
Physical Review E (Phys. Rev. E), 2022
J. Rocks
Pankaj Mehta
137
12
0
10 Mar 2022
On Optimal Early Stopping: Over-informative versus Under-informative Parametrization
Ruoqi Shen
Liyao (Mars) Gao
Yi-An Ma
250
16
0
20 Feb 2022
Geometric Regularization from Overparameterization
Nicholas J. Teague
166
1
0
18 Feb 2022
Stochastic Perturbations of Tabular Features for Non-Deterministic Inference with Automunge
Nicholas J. Teague
AAML
184
1
0
18 Feb 2022
Model, sample, and epoch-wise descents: exact solution of gradient flow in the random feature model
Neural Information Processing Systems (NeurIPS), 2021
A. Bodin
N. Macris
278
15
0
22 Oct 2021
On the Double Descent of Random Features Models Trained with SGD
Fanghui Liu
Johan A. K. Suykens
Volkan Cevher
MLT
476
11
0
13 Oct 2021
Random matrices in service of ML footprint: ternary random features with no performance loss
Hafiz Tiomoko Ali
Zhenyu Liao
Romain Couillet
229
8
0
05 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
262
77
0
06 Sep 2021
On the Role of Optimization in Double Descent: A Least Squares Study
Neural Information Processing Systems (NeurIPS), 2021
Ilja Kuzborskij
Csaba Szepesvári
Omar Rivasplata
Amal Rannen-Triki
Razvan Pascanu
117
10
0
27 Jul 2021
Taxonomizing local versus global structure in neural network loss landscapes
Neural Information Processing Systems (NeurIPS), 2021
Yaoqing Yang
Liam Hodgkinson
Ryan Theisen
Joe Zou
Joseph E. Gonzalez
Kannan Ramchandran
Michael W. Mahoney
367
43
0
23 Jul 2021
Towards an Understanding of Benign Overfitting in Neural Networks
Zhu Li
Zhi Zhou
Arthur Gretton
MLT
250
35
0
06 Jun 2021
The Geometry of Over-parameterized Regression and Adversarial Perturbations
J. Rocks
Pankaj Mehta
AAML
176
10
0
25 Mar 2021
Noisy Recurrent Neural Networks
Neural Information Processing Systems (NeurIPS), 2021
Soon Hoe Lim
N. Benjamin Erichson
Liam Hodgkinson
Michael W. Mahoney
295
66
0
09 Feb 2021
Provable Benefits of Overparameterization in Model Compression: From Double Descent to Pruning Neural Networks
AAAI Conference on Artificial Intelligence (AAAI), 2020
Xiangyu Chang
Yingcong Li
Samet Oymak
Christos Thrampoulidis
281
58
0
16 Dec 2020
Risk-Monotonicity in Statistical Learning
Neural Information Processing Systems (NeurIPS), 2020
Zakaria Mhammedi
559
8
0
28 Nov 2020
Sparse sketches with small inversion bias
Annual Conference Computational Learning Theory (COLT), 2020
Michal Derezinski
Zhenyu Liao
Guang Cheng
Michael W. Mahoney
464
25
0
21 Nov 2020
Determinantal Point Processes Implicitly Regularize Semi-parametric Regression Problems
SIAM Journal on Mathematics of Data Science (SIMODS), 2020
Michaël Fanuel
J. Schreurs
Johan A. K. Suykens
147
4
0
13 Nov 2020
Memorizing without overfitting: Bias, variance, and interpolation in over-parameterized models
Physical Review Research (PRResearch), 2020
J. Rocks
Pankaj Mehta
499
56
0
26 Oct 2020
Failures of model-dependent generalization bounds for least-norm interpolation
Journal of machine learning research (JMLR), 2020
Peter L. Bartlett
Philip M. Long
385
31
0
16 Oct 2020
What causes the test error? Going beyond bias-variance via ANOVA
Journal of machine learning research (JMLR), 2020
Licong Lin
Guang Cheng
284
35
0
11 Oct 2020
Kernel regression in high dimensions: Refined analysis beyond double descent
Fanghui Liu
Zhenyu Liao
Johan A. K. Suykens
345
49
0
06 Oct 2020
Benign overfitting in ridge regression
Alexander Tsigler
Peter L. Bartlett
304
196
0
29 Sep 2020
Provable More Data Hurt in High Dimensional Least Squares Estimator
Zeng Li
Chuanlong Xie
Qinwen Wang
132
6
0
14 Aug 2020
Understanding Implicit Regularization in Over-Parameterized Single Index Model
Journal of the American Statistical Association (JASA), 2020
Jianqing Fan
Zhuoran Yang
Mengxin Yu
315
22
0
16 Jul 2020
Debiasing Distributed Second Order Optimization with Surrogate Sketching and Scaled Regularization
Michal Derezinski
Burak Bartan
Mert Pilanci
Michael W. Mahoney
166
27
0
02 Jul 2020
Ensemble Kernel Methods, Implicit Regularization and Determinantal Point Processes
J. Schreurs
Michaël Fanuel
Johan A. K. Suykens
291
2
0
24 Jun 2020
Good Classifiers are Abundant in the Interpolating Regime
Ryan Theisen
Jason M. Klusowski
Michael W. Mahoney
159
2
0
22 Jun 2020
Precise expressions for random projections: Low-rank approximation and randomized Newton
Michal Derezinski
Feynman T. Liang
Zhenyu A. Liao
Michael W. Mahoney
412
24
0
18 Jun 2020
1
2
Next
