Snapshot Ensembles: Train 1, get M for free

Snapshot Ensembles: Train 1, get M for free

1 April 2017

Gao Huang

John E. Hopcroft

Kilian Q. Weinberger

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Papers citing "Snapshot Ensembles: Train 1, get M for free"

8 / 458 papers shown

Title
Mini-batch Tempered MCMC Dangna Li W. Wong 318 9 0 31 Jul 2017
Memory-Efficient Implementation of DenseNets Geoff Pleiss Danlu Chen Gao Huang Tongcheng Li Laurens van der Maaten Kilian Q. Weinberger 151 169 0 21 Jul 2017
Parle: parallelizing stochastic gradient descent Pratik Chaudhari Carlo Baldassi R. Zecchina Stefano Soatto Ameet Talwalkar Adam M. Oberman ODL FedML 164 23 0 03 Jul 2017
Efficient variational Bayesian neural network ensembles for outlier detection Nick Pawlowski Miguel Jaques Ben Glocker BDL UQCV 80 14 0 20 Mar 2017
Stability of Topic Modeling via Matrix FactorizationExpert systems with applications (ESWA), 2017 Mark Belford Brian Mac Namee Derek Greene 155 88 0 23 Feb 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 1.3K 6,640 0 05 Dec 2016
Temporal Ensembling for Semi-Supervised LearningInternational Conference on Learning Representations (ICLR), 2016 S. Laine Timo Aila UQCV 488 2,740 0 07 Oct 2016
SGDR: Stochastic Gradient Descent with Warm Restarts I. Loshchilov Katharina Eggensperger ODL 856 9,437 0 13 Aug 2016