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We study nonconvex finite-sum problems and analyze stochastic variance reduced gradient (SVRG) methods for them.
A stochastic approximation method
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Understanding the difficulty of training deep feedforward neural networks
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Incremental gradient, subgradient, and proximal methods for convex optimization: A survey
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Stochastic approximation methods for constrained and unconstrained systems , volume 26
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A stochastic PCA and SVD algorithm with an exponential convergence rate
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A proximal stochastic gradient method with progressive variance reduction
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Escaping from saddle points - online stochastic gradient for tensor decomposition
Ge, Rong, Huang, Furong, Jin, Chi, and Yuan, Yang · 2015
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Beyond convexity: Stochastic quasi-convex optimization
Hazan, Elad, Levy, Kfir, and Shalev-Shwartz, Shai · 2015
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Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting
Konečný, Jakub, Liu, Jie, Richtárik, Peter, and Takáč, Martin · 2015
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Konečný, Jakub and Richtárik, Peter · 2013
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Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization
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Shalev-Shwartz, Shai · 2015
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