A fast dual proximal gradient algorithm for convex minimization and applications

We consider the convex composite problem of minimizing the sum of a strongly convex function and a general extended valued convex function. We present a dual-based proximal gradient scheme for solving this problem. We show that although the rate of convergence of the dual objective function sequence...

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Veröffentlicht in:Operations research letters Jg. 42; H. 1; S. 1 - 6
Hauptverfasser: Beck, Amir, Teboulle, Marc
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 01.01.2014
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Abstract We consider the convex composite problem of minimizing the sum of a strongly convex function and a general extended valued convex function. We present a dual-based proximal gradient scheme for solving this problem. We show that although the rate of convergence of the dual objective function sequence converges to the optimal value with the rate O(1/k2), the rate of convergence of the primal sequence is of the order O(1/k).
AbstractList We consider the convex composite problem of minimizing the sum of a strongly convex function and a general extended valued convex function. We present a dual-based proximal gradient scheme for solving this problem. We show that although the rate of convergence of the dual objective function sequence converges to the optimal value with the rate O(1/k2), the rate of convergence of the primal sequence is of the order O(1/k).
We consider the convex composite problem of minimizing the sum of a strongly convex function and a general extended valued convex function. We present a dual-based proximal gradient scheme for solving this problem. We show that although the rate of convergence of the dual objective function sequence converges to the optimal value with the rate O(1/k super(2))O(1/k2), the rate of convergence of the primal sequence is of the order O(1/k)O(1/k).
Author Teboulle, Marc
Beck, Amir
Author_xml – sequence: 1
  givenname: Amir
  surname: Beck
  fullname: Beck, Amir
  email: becka@ie.technion.ac.il
  organization: Faculty of Industrial Engineering and Management, Technion - Israel Institute of Technology, Haifa, Israel
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  givenname: Marc
  surname: Teboulle
  fullname: Teboulle, Marc
  email: teboulle@post.tau.ac.il
  organization: School of Mathematical Sciences, Tel-Aviv University, Ramat-Aviv, Israel
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Issue 1
Keywords Fast gradient methods
Dual-based methods
Rate of convergence
Convex optimization
Language English
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Snippet We consider the convex composite problem of minimizing the sum of a strongly convex function and a general extended valued convex function. We present a...
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SubjectTerms Algorithms
Convergence
Convex optimization
Dual-based methods
Fast gradient methods
Minimization
Operations research
Optimization
Rate of convergence
Sequences
Title A fast dual proximal gradient algorithm for convex minimization and applications
URI https://dx.doi.org/10.1016/j.orl.2013.10.007
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Volume 42
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