Publication | Closed Access
On global and local convergence of half-quadratic algorithms
87
Citations
33
References
2006
Year
Numerical AnalysisMathematical ProgrammingGr FormEngineeringComputer EngineeringImproved Convergence RateComputational ComplexityBetter Convergence RateParallel ProgrammingComputer ScienceSemi-definite OptimizationSemidefinite ProgrammingParallel ComputingLarge Scale OptimizationApproximation TheoryHalf-quadratic AlgorithmsQuadratic Programming
This paper provides original results on the global and local convergence properties of half-quadratic (HQ) algorithms resulting from the Geman and Yang (GY) and Geman and Reynolds (GR) primal-dual constructions. First, we show that the convergence domain of the GY algorithm can be extended with the benefit of an improved convergence rate. Second, we provide a precise comparison of the convergence rates for both algorithms. This analysis shows that the GR form does not benefit from a better convergence rate in general. Moreover, the GY iterates often take advantage of a low cost implementation. In this case, the GY form is usually faster than the GR form from the CPU time viewpoint.
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