Weight Expansion: A New Perspective on Dropout and Generalization

23 January 2022

Papers citing "Weight Expansion: A New Perspective on Dropout and Generalization"

9 / 9 papers shown

Title
Enhancing Adversarial Training with Second-Order Statistics of Weights Gao Jin Xinping Yi Wei Huang S. Schewe Xiaowei Huang AAML 8 46 0 11 Mar 2022
Learning PAC-Bayes Priors for Probabilistic Neural Networks Maria Perez-Ortiz Omar Rivasplata Benjamin Guedj M. Gleeson Jingyu Zhang John Shawe-Taylor M. Bober J. Kittler UQCV 43 31 0 21 Sep 2021
AutoDropout: Learning Dropout Patterns to Regularize Deep Networks Hieu H. Pham Quoc V. Le 55 50 0 05 Jan 2021
Information-Theoretic Generalization Bounds for SGLD via Data-Dependent Estimates Jeffrey Negrea Mahdi Haghifam Gintare Karolina Dziugaite Ashish Khisti Daniel M. Roy FedML 105 146 0 06 Nov 2019
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 273 2,696 0 15 Sep 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,042 0 06 Jun 2015
Norm-Based Capacity Control in Neural Networks Behnam Neyshabur Ryota Tomioka Nathan Srebro 111 551 0 27 Feb 2015
Convolutional Neural Networks for Sentence Classification Yoon Kim AILaw VLM 238 13,283 0 25 Aug 2014
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 240 7,597 0 03 Jul 2012