What training reveals about neural network complexity

8 June 2021

Papers citing "What training reveals about neural network complexity"

6 / 6 papers shown

Title
When Deep Learning Meets Polyhedral Theory: A Survey Joey Huchette Gonzalo Muñoz Thiago Serra Calvin Tsay AI4CE 94 32 0 29 Apr 2023
On the generalization of learning algorithms that do not converge N. Chandramoorthy Andreas Loukas Khashayar Gatmiry Stefanie Jegelka MLT 19 11 0 16 Aug 2022
Dropout: Explicit Forms and Capacity Control R. Arora Peter L. Bartlett Poorya Mianjy Nathan Srebro 64 37 0 06 Mar 2020
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
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,145 0 06 Jun 2015
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,638 0 03 Jul 2012