The Dynamics of Learning: A Random Matrix Approach

30 May 2018

Papers citing "The Dynamics of Learning: A Random Matrix Approach"

11 / 11 papers shown

Title
High-dimensional analysis of ridge regression for non-identically distributed data with a variance profile Jérémie Bigot Issa-Mbenard Dabo Camille Male 29 4 0 29 Mar 2024
Model, sample, and epoch-wise descents: exact solution of gradient flow in the random feature model A. Bodin N. Macris 29 13 0 22 Oct 2021
Dissipative Deep Neural Dynamical Systems Ján Drgoňa Soumya Vasisht Aaron Tuor D. Vrabie 19 6 0 26 Nov 2020
An analytic theory of shallow networks dynamics for hinge loss classification Franco Pellegrini Giulio Biroli 19 19 0 19 Jun 2020
When Does Preconditioning Help or Hurt Generalization? S. Amari Jimmy Ba Roger C. Grosse Xuechen Li Atsushi Nitanda Taiji Suzuki Denny Wu Ji Xu 34 32 0 18 Jun 2020
Spectra of the Conjugate Kernel and Neural Tangent Kernel for linear-width neural networks Z. Fan Zhichao Wang 29 72 0 25 May 2020
Scaling description of generalization with number of parameters in deep learning Mario Geiger Arthur Jacot S. Spigler Franck Gabriel Levent Sagun Stéphane dÁscoli Giulio Biroli Clément Hongler M. Wyart 39 194 0 06 Jan 2019
Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning Charles H. Martin Michael W. Mahoney AI4CE 30 190 0 02 Oct 2018
On the Learning Dynamics of Deep Neural Networks Rémi Tachet des Combes Mohammad Pezeshki Samira Shabanian Aaron Courville Yoshua Bengio 8 38 0 18 Sep 2018
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 281 2,888 0 15 Sep 2016
The Loss Surfaces of Multilayer Networks A. Choromańska Mikael Henaff Michaël Mathieu Gerard Ben Arous Yann LeCun ODL 179 1,185 0 30 Nov 2014