Multiscale Annealing and Robustness: Fast Heuristics for Large Scale Non-linear Optimization

Joachim M. Buhmann and Jan Puzicha
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Joachim M. Buhmann: Rheinische Friedrich-Wilhelm Universität, Institut für Informatik
Jan Puzicha: University of California, Department of Computer Science

A chapter in Online Optimization of Large Scale Systems, 2001, pp 779-801 from Springer

Abstract: Abstract Multiscale Annealing is an extension of the idea of deterministic annealing which link the approximation quality of the algorithms to their effective spatial resolution. The optimization variables of a particular scale are linked together to reduce the spatial resolution, and, thereby, to simplify the computational complexity of the optimization task. Robustness and efficiency issues are discussed in this article on research questions of annealing techniques.

Keywords: Cost Function; Random Graph; Coarse Grid; Cluster Solution; Markov Random Field (search for similar items in EconPapers)
Date: 2001
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DOI: 10.1007/978-3-662-04331-8_37

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