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In this paper, we develop new first-order method for composite non-convex minimization problems with simple constraints and inexact oracle.
Gradient methods for the minimisation of functionals
Boris Polyak · 1963
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Boris Polyak · 1987
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Introductory Lectures on Convex Optimization: a basic course
Yurii Nesterov · 2004
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Smooth minimization of non-smooth functions
Yurii Nesterov · 2005
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Cubic regularization of newton method and its global performance
Yurii Nesterov and Boris Polyak · 2006
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Smooth optimization with approximate gradient
Alexandre d’Aspremont · 2008
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First-order methods of smooth convex optimization with inexact oracle
Olivier Devolder, François Glineur, and Yurii Nesterov · 2014
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Lectures on Modern Convex Optimization (Lecture Notes)
Aaron Ben-Tal and Arkadi Nemirovski · 2015
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Generalized uniformly optimal methods for nonlinear programming
Saeed Ghadimi, Guanghui Lan, and Hongchao Zhang · 2015
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Universal gradient methods for convex optimization problems
Yurii Nesterov · 2015
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Learning supervised pagerank with gradient-based and gradient-free optimization methods
Lev Bogolubsky, Pavel Dvurechensky, Alexander Gasnikov, Gleb Gusev, Yurii Nesterov, Andrey Raigorodskii, Aleksey Tikhonov, and Maksim Zhukovskii · 2016
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Stochastic intermediate gradient method for convex problems with stochastic inexact oracle
Pavel Dvurechensky and Alexander Gasnikov · 2016
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Accelerated gradient methods for nonconvex nonlinear and stochastic programming
Saeed Ghadimi and Guanghui Lan · 2016
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Mini-batch stochastic approximation methods for nonconvex stochastic composite optimization
Saeed Ghadimi, Guanghui Lan, and Hongchao Zhang · 2016
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