Implicit Regularization of Stochastic Gradient Descent in Natural Language Processing: Observations and Implications

1 November 2018

Papers citing "Implicit Regularization of Stochastic Gradient Descent in Natural Language Processing: Observations and Implications"

9 / 9 papers shown

Title
Deep Learning Optimization Using Self-Adaptive Weighted Auxiliary Variables Yaru Liu Yiqi Gu Michael K. Ng ODL 67 0 0 30 Apr 2025
Why Deep Learning Generalizes Benjamin L. Badger TDI AI4CE 25 3 0 17 Nov 2022
The Discovery of Dynamics via Linear Multistep Methods and Deep Learning: Error Estimation Q. Du Yiqi Gu Haizhao Yang Chao Zhou 26 20 0 21 Mar 2021
Reproducing Activation Function for Deep Learning Senwei Liang Liyao Lyu Chunmei Wang Haizhao Yang 36 21 0 13 Jan 2021
On Computability, Learnability and Extractability of Finite State Machines from Recurrent Neural Networks Reda Marzouk 12 2 0 10 Sep 2020
Big-Data Science in Porous Materials: Materials Genomics and Machine Learning Kevin Maik Jablonka D. Ongari S. M. Moosavi B. Smit AI4CE 31 351 0 18 Jan 2020
Second-order Information in First-order Optimization Methods Yuzheng Hu Licong Lin Shange Tang ODL 30 2 0 20 Dec 2019
Gaussian Mean Field Regularizes by Limiting Learned Information Julius Kunze Louis Kirsch H. Ritter David Barber FedML MLT 16 2 0 12 Feb 2019
Convolutional Neural Networks for Sentence Classification Yoon Kim AILaw VLM 312 13,377 0 25 Aug 2014