Calcolo

, Volume 54, Issue 1, pp 207–224 | Cite as

Greedy Strategies for Convex Optimization

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Abstract

We investigate two greedy strategies for finding an approximation to the minimum of a convex function E defined on a Hilbert space H. We prove convergence rates for these algorithms under suitable conditions on the objective function E. These conditions involve the behavior of the modulus of smoothness and the modulus of uniform convexity of E.

Keywords

Greedy algorithms Convex optimization Rates of convergence 

Mathematics Subject Classification

65K05 90C25 41A46 
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Copyright information

© Springer-Verlag Italia 2016

Authors and Affiliations

  1. 1.WorldQuant LLCHanoiVietnam
  2. 2.Department of MathematicsTexas A&M UniversityCollege StationUSA

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