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We consider optimizing a function smooth convex function $f$ that is the average of a set of differentiable functions $f_i$, under the assumption considered by Solodov [1998] and Tseng [1998] that the norm of each gradient $f_i'$ is bounded by a linear function of the norm of the average gradient $f'$.
Efficient methods in convex programming
A. Nemirovski · 1994
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Incremental gradient algorithms with stepsizes bounded away from zero
M. Solodov · 1998
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An incremental gradient(-projection) method with momentum term and adaptive stepsize rule
P. Tseng · 1998
Earlier work this paper cites.
Nonlinear programming
D. Bertsekas · 1999
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Introductory lectures on convex optimization: A basic course
Y. Nesterov · 2004
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Linear and nonlinear programming
D. Luenberger and Y. Ye · 2008
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Robust stochastic approximation approach to stochastic programming
A. Nemirovski, A. Juditsky, G. Lan, and A. Shapiro · 2009
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