To Drop or Not to Drop: Robustness, Consistency and Differential Privacy Properties of Dropout

6 March 2015

Papers citing "To Drop or Not to Drop: Robustness, Consistency and Differential Privacy Properties of Dropout"

5 / 5 papers shown

Title
On the utility and protection of optimization with differential privacy and classic regularization techniques Eugenio Lomurno Matteo matteucci 15 9 0 07 Sep 2022
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 28 4,021 0 18 Oct 2016
Ensemble Robustness and Generalization of Stochastic Deep Learning Algorithms Tom Zahavy Bingyi Kang Alex Sivak Jiashi Feng Huan Xu Shie Mannor OOD AAML 29 12 0 07 Feb 2016
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes Ohad Shamir Tong Zhang 99 570 0 08 Dec 2012
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,634 0 03 Jul 2012