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ABSTRACT We establish linear convergence rates for a certain class of extrapolated fixed point algorithms which are based on dynamic string-averaging methods in a real Hilbert space. This applies, in… Click to show full abstract
ABSTRACT We establish linear convergence rates for a certain class of extrapolated fixed point algorithms which are based on dynamic string-averaging methods in a real Hilbert space. This applies, in particular, to the extrapolated simultaneous and cyclic cutter methods. Our analysis covers the cases of both metric and subgradient projections.
Keywords:
extrapolated fixed;
linear convergence;
convergence rates;
point algorithms;
fixed point
Journal Title: Optimization
Year Published: 2018
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Journal Title: Optimization
Year Published: 2018
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!