Risk Bounds for Over-parameterized Maximum Margin Classification on
Sub-Gaussian Mixtures

Risk Bounds for Over-parameterized Maximum Margin Classification on Sub-Gaussian Mixtures

28 April 2021

Quanquan Gu

Papers citing "Risk Bounds for Over-parameterized Maximum Margin Classification on Sub-Gaussian Mixtures"

10 / 10 papers shown

Title
Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality Marko Medvedev Gal Vardi Nathan Srebro 68 3 0 05 Sep 2024
General Loss Functions Lead to (Approximate) Interpolation in High Dimensions Kuo-Wei Lai Vidya Muthukumar 26 5 0 13 Mar 2023
Malign Overfitting: Interpolation Can Provably Preclude Invariance Yoav Wald G. Yona Uri Shalit Y. Carmon 17 5 0 28 Nov 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
Benign Overfitting in Adversarially Robust Linear Classification Jinghui Chen Yuan Cao Quanquan Gu AAML SILM 31 10 0 31 Dec 2021
Classification and Adversarial examples in an Overparameterized Linear Model: A Signal Processing Perspective Adhyyan Narang Vidya Muthukumar A. Sahai SILM AAML 33 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
Towards an Understanding of Benign Overfitting in Neural Networks Zhu Li Zhi-Hua Zhou A. Gretton MLT 33 35 0 06 Jun 2021
On the proliferation of support vectors in high dimensions Daniel J. Hsu Vidya Muthukumar Ji Xu 24 42 0 22 Sep 2020