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Understanding the Role of Momentum in Stochastic Gradient Methods


Oct 30, 2019
Igor Gitman, Hunter Lang, Pengchuan Zhang, Lin Xiao

* 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada 

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OpenSeq2Seq: extensible toolkit for distributed and mixed precision training of sequence-to-sequence models


May 25, 2018
Oleksii Kuchaiev, Boris Ginsburg, Igor Gitman, Vitaly Lavrukhin, Carl Case, Paulius Micikevicius

* to be presented at Workshop for Natural Language Processing Open Source Software (NLP-OSS), co-located with ACL2018 

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Novel Prediction Techniques Based on Clusterwise Linear Regression


Apr 28, 2018
Igor Gitman, Jieshi Chen, Eric Lei, Artur Dubrawski


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Convergence Analysis of Gradient Descent Algorithms with Proportional Updates


Jan 09, 2018
Igor Gitman, Deepak Dilipkumar, Ben Parr

* Source code (uses TensorFlow): https://github.com/bparr/lars 

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Comparison of Batch Normalization and Weight Normalization Algorithms for the Large-scale Image Classification


Oct 07, 2017
Igor Gitman, Boris Ginsburg


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Large Batch Training of Convolutional Networks


Sep 13, 2017
Yang You, Igor Gitman, Boris Ginsburg


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