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Stochastic Gradient Descent as Approximate Bayesian Inference

13 April 2017

Matthew D. Hoffman

Papers citing "Stochastic Gradient Descent as Approximate Bayesian Inference"

27 / 327 papers shown

Title
Averaging Weights Leads to Wider Optima and Better Generalization Pavel Izmailov Dmitrii Podoprikhin T. Garipov Dmitry Vetrov A. Wilson FedML MoMe 153 1,672 0 14 Mar 2018
WHAI: Weibull Hybrid Autoencoding Inference for Deep Topic Modeling Hao Zhang Bo Chen D. Guo Mingyuan Zhou BDL 80 118 0 04 Mar 2018
The Anisotropic Noise in Stochastic Gradient Descent: Its Behavior of Escaping from Sharp Minima and Regularization Effects Zhanxing Zhu Jingfeng Wu Ting Yu Lei Wu Jin Ma 81 40 0 01 Mar 2018
A Walk with SGD Chen Xing Devansh Arpit Christos Tsirigotis Yoshua Bengio 96 119 0 24 Feb 2018
An Alternative View: When Does SGD Escape Local Minima? Robert D. Kleinberg Yuanzhi Li Yang Yuan MLT 95 317 0 17 Feb 2018
HiGrad: Uncertainty Quantification for Online Learning and Stochastic Approximation Weijie J. Su Yuancheng Zhu 92 38 0 13 Feb 2018
Improving Generalization Performance by Switching from Adam to SGD N. Keskar R. Socher ODL 105 524 0 20 Dec 2017
Statistical Inference for the Population Landscape via Moment Adjusted Stochastic Gradients Tengyuan Liang Weijie Su 72 21 0 20 Dec 2017
Vprop: Variational Inference using RMSprop Mohammad Emtiyaz Khan Zuozhu Liu Voot Tangkaratt Y. Gal BDL 73 17 0 04 Dec 2017
Asymptotic Analysis via Stochastic Differential Equations of Gradient Descent Algorithms in Statistical and Computational Paradigms Yazhen Wang 87 17 0 27 Nov 2017
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 230 698 0 15 Nov 2017
Three Factors Influencing Minima in SGD Stanislaw Jastrzebski Zachary Kenton Devansh Arpit Nicolas Ballas Asja Fischer Yoshua Bengio Amos Storkey 85 463 0 13 Nov 2017
Don't Decay the Learning Rate, Increase the Batch Size Samuel L. Smith Pieter-Jan Kindermans Chris Ying Quoc V. Le ODL 130 996 0 01 Nov 2017
Deep Neural Networks as Gaussian Processes Jaehoon Lee Yasaman Bahri Roman Novak S. Schoenholz Jeffrey Pennington Jascha Narain Sohl-Dickstein UQCV BDL 160 1,100 0 01 Nov 2017
Fraternal Dropout Konrad Zolna Devansh Arpit Dendi Suhubdy Yoshua Bengio 69 53 0 31 Oct 2017
Techreport: Time-sensitive probabilistic inference for the edge Christian D. Weilbach Annette Bieniusa 46 0 0 30 Oct 2017
Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks Pratik Chaudhari Stefano Soatto MLT 104 304 0 30 Oct 2017
A Bayesian Perspective on Generalization and Stochastic Gradient Descent Samuel L. Smith Quoc V. Le BDL 126 253 0 17 Oct 2017
Regularizing and Optimizing LSTM Language Models Stephen Merity N. Keskar R. Socher 178 1,098 0 07 Aug 2017
Bridging the Gap between Constant Step Size Stochastic Gradient Descent and Markov Chains Aymeric Dieuleveut Alain Durmus Francis R. Bach 89 156 0 20 Jul 2017
Acceleration and Averaging in Stochastic Mirror Descent Dynamics Walid Krichene Peter L. Bartlett 38 10 0 19 Jul 2017
Statistical inference using SGD Tianyang Li Liu Liu Anastasios Kyrillidis Constantine Caramanis FedML 48 38 0 21 May 2017
Determinantal Point Processes for Mini-Batch Diversification Cheng Zhang Hedvig Kjellström Stephan Mandt 85 35 0 01 May 2017
Introspective Generative Modeling: Decide Discriminatively Justin Lazarow Long Jin Zhuowen Tu 31 2 0 25 Apr 2017
Introspective Classification with Convolutional Nets Long Jin Justin Lazarow Zhuowen Tu BDL 24 2 0 25 Apr 2017
Efficient variational Bayesian neural network ensembles for outlier detection Nick Pawlowski Miguel Jaques Ben Glocker BDL UQCV 47 13 0 20 Mar 2017
Statistics of Robust Optimization: A Generalized Empirical Likelihood Approach John C. Duchi Peter Glynn Hongseok Namkoong 142 325 0 11 Oct 2016