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2406.03171
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High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization
5 June 2024
Yihang Chen
Fanghui Liu
Taiji Suzuki
Volkan Cevher
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Papers citing
"High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization"
12 / 12 papers shown
Title
Understanding Why Generalized Reweighting Does Not Improve Over ERM
Runtian Zhai
Chen Dan
Zico Kolter
Pradeep Ravikumar
OOD
59
28
0
28 Jan 2022
Covariate Shift in High-Dimensional Random Feature Regression
Nilesh Tripuraneni
Ben Adlam
Jeffrey Pennington
OOD
45
24
0
16 Nov 2021
Learning with invariances in random features and kernel models
Song Mei
Theodor Misiakiewicz
Andrea Montanari
OOD
100
91
0
25 Feb 2021
Generalization error of random features and kernel methods: hypercontractivity and kernel matrix concentration
Song Mei
Theodor Misiakiewicz
Andrea Montanari
84
112
0
26 Jan 2021
When Do Neural Networks Outperform Kernel Methods?
Behrooz Ghorbani
Song Mei
Theodor Misiakiewicz
Andrea Montanari
91
189
0
24 Jun 2020
On the Optimal Weighted
ℓ
2
\ell_2
ℓ
2
Regularization in Overparameterized Linear Regression
Denny Wu
Ji Xu
70
123
0
10 Jun 2020
Rethinking Importance Weighting for Deep Learning under Distribution Shift
Tongtong Fang
Nan Lu
Gang Niu
Masashi Sugiyama
67
139
0
08 Jun 2020
Linearized two-layers neural networks in high dimension
Behrooz Ghorbani
Song Mei
Theodor Misiakiewicz
Andrea Montanari
MLT
60
243
0
27 Apr 2019
Surprises in High-Dimensional Ridgeless Least Squares Interpolation
Trevor Hastie
Andrea Montanari
Saharon Rosset
Robert Tibshirani
194
746
0
19 Mar 2019
Marginal Singularity, and the Benefits of Labels in Covariate-Shift
Samory Kpotufe
Guillaume Martinet
138
96
0
05 Mar 2018
Orthogonal Random Features
Felix X. Yu
A. Suresh
K. Choromanski
D. Holtmann-Rice
Sanjiv Kumar
86
222
0
28 Oct 2016
Ridge regression and asymptotic minimax estimation over spheres of growing dimension
Lee H. Dicker
74
74
0
15 Jan 2016
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