Large-scale learning with AdaGrad on Spark

Stochastic Gradient Descent (SGD) is a simple yet very efficient online learning algorithm for optimizing convex (and often non-convex) functions and one of the most popular stochastic optimization methods in machine learning today. One drawback of SGD is that it is sensitive to the learning rate hy...

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Bibliographic Details

Published in:	2015 IEEE International Conference on Big Data (Big Data) pp. 2828 - 2830
Main Authors:	Hadgu, Asmelash Teka, Nigam, Aastha, Diaz-Aviles, Ernesto
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.10.2015
Subjects:	Adaptive gradient Aggregates Distributed machine learning History Spark Sparks Stochastic processes Support vector machines Training
Online Access:	Get full text
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