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Recently, {\it stochastic momentum} methods have been widely adopted in training deep neural networks.
Some methods of speeding up the convergence of iteration methods
B. T. Polyak · 1964
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A method of solving a convex programming problem with convergence rate O(1/sqr(k))
Yurii Nesterov · 1983
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Introductory lectures on convex optimization : a basic course
Yurii Nesterov · 2004
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Stochastic first- and zeroth-order methods for nonconvex stochastic programming
Saeed Ghadimi and Guanghui Lan · 2013
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On the importance of initialization and momentum in deep learning
Ilya Sutskever, James Martens, George E. Dahl, and Geoffrey E. Hinton · 2013
Cited alongside, same era.
Global convergence of the heavy-ball method for convex optimization
Euhanna Ghadimi, Hamid Reza Feyzmahdavian, and Mikael Johansson · 2014
Cited alongside, same era.
ipiano: Inertial proximal algorithm for nonconvex optimization
Peter Ochs, Yunjin Chen, Thomas Brox, and Thomas Pock · 2014
Cited alongside, same era.
ipiasco: Inertial proximal algorithm for strongly convex optimization
Peter Ochs, Thomas Brox, and Thomas Pock · 2015
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Accelerated gradient methods for nonconvex nonlinear and stochastic programming
Saeed Ghadimi and Guanghui Lan · 2016
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Stochastic variance reduction for nonconvex optimization
Sashank J. Reddi, Ahmed Hefny, Suvrit Sra, Barnabás Póczos, and Alexander J. Smola · 2016
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Variance reduction for faster non-convex optimization
Zeyuan Allen Zhu and Elad Hazan · 2016
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