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 31 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 37 13 0 22 Oct 2021
Dissipative Deep Neural Dynamical Systems Ján Drgoňa Soumya Vasisht Aaron Tuor D. Vrabie 21 7 0 26 Nov 2020
An analytic theory of shallow networks dynamics for hinge loss classification Franco Pellegrini Giulio Biroli 35 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 36 32 0 18 Jun 2020
Spectra of the Conjugate Kernel and Neural Tangent Kernel for linear-width neural networks Z. Fan Zhichao Wang 44 71 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 49 195 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 35 191 0 02 Oct 2018
On the Learning Dynamics of Deep Neural Networks Rémi Tachet des Combes Mohammad Pezeshki Samira Shabanian Aaron Courville Yoshua Bengio 16 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 308 2,890 0 15 Sep 2016
The Loss Surfaces of Multilayer Networks A. Choromańska Mikael Henaff Michaël Mathieu Gerard Ben Arous Yann LeCun ODL 183 1,185 0 30 Nov 2014