Dropout as a Low-Rank Regularizer for Matrix Factorization

13 October 2017

Papers citing "Dropout as a Low-Rank Regularizer for Matrix Factorization"

12 / 12 papers shown

Title
Reasoning Bias of Next Token Prediction Training Pengxiao Lin Zhongwang Zhang Zhi-Qin John Xu LRM 94 2 0 21 Feb 2025
Exact Solutions of a Deep Linear Network Liu Ziyin Botao Li Xiangmin Meng ODL 19 21 0 10 Feb 2022
Stochastic Neural Networks with Infinite Width are Deterministic Liu Ziyin Hanlin Zhang Xiangming Meng Yuting Lu Eric P. Xing Masakuni Ueda 26 3 0 30 Jan 2022
Avoiding Overfitting: A Survey on Regularization Methods for Convolutional Neural Networks C. F. G. Santos João Paulo Papa 24 211 0 10 Jan 2022
Architectural Adversarial Robustness: The Case for Deep Pursuit George Cazenavette Calvin Murdock Simon Lucey AAML 34 23 0 29 Nov 2020
Deep matrix factorizations Pierre De Handschutter Nicolas Gillis Xavier Siebert BDL 28 40 0 01 Oct 2020
Dropout: Explicit Forms and Capacity Control R. Arora Peter L. Bartlett Poorya Mianjy Nathan Srebro 64 37 0 06 Mar 2020
An ETF view of Dropout regularization Dor Bank Raja Giryes 8 4 0 14 Oct 2018
On the Implicit Bias of Dropout Poorya Mianjy R. Arora René Vidal 24 66 0 26 Jun 2018
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 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 7,636 0 03 Jul 2012
Convex Sparse Matrix Factorizations Francis R. Bach Julien Mairal Jean Ponce 137 143 0 10 Dec 2008