Memorizing without overfitting: Bias, variance, and interpolation in over-parameterized models

26 October 2020

Papers citing "Memorizing without overfitting: Bias, variance, and interpolation in over-parameterized models"

4 / 4 papers shown

Title
Breaking Neural Network Scaling Laws with Modularity Akhilan Boopathy Sunshine Jiang William Yue Jaedong Hwang Abhiram Iyer Ila Fiete OOD 39 2 0 09 Sep 2024
Learning through atypical "phase transitions" in overparameterized neural networks Carlo Baldassi Clarissa Lauditi Enrico M. Malatesta R. Pacelli Gabriele Perugini R. Zecchina 26 26 0 01 Oct 2021
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond Fanghui Liu Xiaolin Huang Yudong Chen Johan A. K. Suykens BDL 34 172 0 23 Apr 2020
Double Trouble in Double Descent : Bias and Variance(s) in the Lazy Regime Stéphane dÁscoli Maria Refinetti Giulio Biroli Florent Krzakala 93 152 0 02 Mar 2020