On the proliferation of support vectors in high dimensions

22 September 2020

Papers citing "On the proliferation of support vectors in high dimensions"

9 / 9 papers shown

Title
Classifying Overlapping Gaussian Mixtures in High Dimensions: From Optimal Classifiers to Neural Nets Khen Cohen Noam Levi Yaron Oz BDL 31 1 0 28 May 2024
Precise Asymptotic Generalization for Multiclass Classification with Overparameterized Linear Models David X. Wu A. Sahai 26 2 0 23 Jun 2023
General Loss Functions Lead to (Approximate) Interpolation in High Dimensions Kuo-Wei Lai Vidya Muthukumar 21 5 0 13 Mar 2023
$Tight bounds for maximum $\ell_1$-margin classifiers$ Tight bounds for maximum $\ell_1$ -margin classifiers Stefan Stojanovic Konstantin Donhauser Fanny Yang 35 0 0 07 Dec 2022
Interpolating Discriminant Functions in High-Dimensional Gaussian Latent Mixtures Xin Bing M. Wegkamp 16 1 0 25 Oct 2022
Deep Linear Networks can Benignly Overfit when Shallow Ones Do Niladri S. Chatterji Philip M. Long 17 8 0 19 Sep 2022
Classification and Adversarial examples in an Overparameterized Linear Model: A Signal Processing Perspective Adhyyan Narang Vidya Muthukumar A. Sahai SILM AAML 31 1 0 27 Sep 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
Classification vs regression in overparameterized regimes: Does the loss function matter? Vidya Muthukumar Adhyyan Narang Vignesh Subramanian M. Belkin Daniel J. Hsu A. Sahai 36 148 0 16 May 2020