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We analyze a fast incremental aggregated gradient method for optimizing nonconvex problems of the form $\min_x \sum_i f_i(x)$.
A stochastic approximation method
Robbins, H. and Monro, S · 1951
Earlier work this paper cites.
Gradient methods for the minimisation of functionals
Polyak, B.T · 1963
Earlier work this paper cites.
Parallel and Distributed Computation: Numerical Methods
Bertsekas, D. and Tsitsiklis, J · 1989
Earlier work this paper cites.
Introductory Lectures On Convex Optimization: A Basic Course
Nesterov, Yurii · 2003
Earlier work this paper cites.
Cubic regularization of newton method and its global performance
Nesterov, Yurii and Polyak, Boris T · 2006
Earlier work this paper cites.
Penalized likelihood regression for generalized linear models with non-quadratic penalties
Antoniadis, Anestis, Gijbels, Irène, and Nikolova, Mila · 2009
Earlier work this paper cites.
Robust stochastic approximation approach to stochastic programming
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Earlier work this paper cites.
Distributed delayed stochastic optimization
Agarwal, Alekh and Duchi, John C · 2011
Earlier work this paper cites.
Incremental gradient, subgradient, and proximal methods for convex optimization: A survey
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Minimizing Finite Sums with the Stochastic Average Gradient
Schmidt, Mark W., Roux, Nicolas Le, and Bach, Francis R · 2013
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On variance reduction in stochastic gradient descent and its asynchronous variants
Reddi, Sashank, Hefny, Ahmed, Sra, Suvrit, Poczos, Barnabas, and Smola, Alex J · 2015
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Shalev-Shwartz, Shai · 2015
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