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Interpolating Greedy and Reluctant Algorithms

2003/09/30 by P. Contucci, C. Giardina', Contucci, P. +7 · 1 citation
Mathematics · Physics and Astronomy · #Disordered Systems and Neural Networks (cond-mat.dis-nn) #FOS: Physical sciences #Mathematical Physics (math-ph) #cond-mat.dis-nn #math-ph #math.MP

paper · pdf · doi:10.48550/arxiv.math-ph/0309063

9 pages. 3 figures

arxiv created 2003/09/30 · arxiv updated 2009/12/01

Abstract

In a standard NP-complete optimization problem we introduce an interpolating algorithm between the quick decrease along the gradient (greedy dynamics) and a slow decrease close to the level curves (reluctant dynamics). We find that for a fixed elapsed computer time the best performance of the optimization is reached at a special value of the interpolation parameter, considerably improving the results of the pure cases greedy and reluctant.

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