A Random Matrix Perspective on Mixtures of Nonlinearities for Deep Learning

2 December 2019

Papers citing "A Random Matrix Perspective on Mixtures of Nonlinearities for Deep Learning"

9 / 9 papers shown

Title
A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks Behrad Moniri Donghwan Lee Hamed Hassani Yan Sun MLT 40 19 0 11 Oct 2023
Demystifying Disagreement-on-the-Line in High Dimensions Dong-Hwan Lee Behrad Moniri Xinmeng Huang Yan Sun Hamed Hassani 21 8 0 31 Jan 2023
A Solvable Model of Neural Scaling Laws A. Maloney Daniel A. Roberts J. Sully 36 51 0 30 Oct 2022
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
Deformed semicircle law and concentration of nonlinear random matrices for ultra-wide neural networks Zhichao Wang Yizhe Zhu 35 18 0 20 Sep 2021
Analysis of One-Hidden-Layer Neural Networks via the Resolvent Method Vanessa Piccolo Dominik Schröder 18 8 0 11 May 2021
Mixed Moments for the Product of Ginibre Matrices Nick Halmagyi Shailesh Lal 16 2 0 20 Jul 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
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Z. Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 716 6,746 0 26 Sep 2016