Strong inductive biases provably prevent harmless interpolation

Strong inductive biases provably prevent harmless interpolation

18 January 2023

Konstantin Donhauser

Papers citing "Strong inductive biases provably prevent harmless interpolation"

11 / 11 papers shown

Title
On the Saturation Effects of Spectral Algorithms in Large Dimensions Weihao Lu Haobo Zhang Yicheng Li Q. Lin 34 1 0 01 Mar 2025
On the Pinsker bound of inner product kernel regression in large dimensions Weihao Lu Jialin Ding Haobo Zhang Qian Lin 34 0 0 02 Sep 2024
Accuracy on the wrong line: On the pitfalls of noisy data for out-of-distribution generalisation Amartya Sanyal Yaxi Hu Yaodong Yu Yian Ma Yixin Wang Bernhard Schölkopf OODD 28 1 0 27 Jun 2024
High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization Yihang Chen Fanghui Liu Taiji Suzuki V. Cevher 29 1 0 05 Jun 2024
The phase diagram of kernel interpolation in large dimensions Haobo Zhang Weihao Lu Qian Lin 36 5 0 19 Apr 2024
Optimal Rate of Kernel Regression in Large Dimensions Weihao Lu Hao Zhang Yicheng Li Manyun Xu Qian Lin 18 4 0 08 Sep 2023
Mind the spikes: Benign overfitting of kernels and neural networks in fixed dimension Moritz Haas David Holzmüller U. V. Luxburg Ingo Steinwart MLT 11 13 0 23 May 2023
Tight bounds for minimum l1-norm interpolation of noisy data Guillaume Wang Konstantin Donhauser Fanny Yang 75 20 0 10 Nov 2021
Harmless interpolation in regression and classification with structured features Andrew D. McRae Santhosh Karnik Mark A. Davenport Vidya Muthukumar 93 11 0 09 Nov 2021
Foolish Crowds Support Benign Overfitting Niladri S. Chatterji Philip M. Long 76 20 0 06 Oct 2021
Learning with invariances in random features and kernel models Song Mei Theodor Misiakiewicz Andrea Montanari OOD 44 89 0 25 Feb 2021