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<p>Piecewise continuous reconstruction of real-valued data can be formulated in terms of nonconvex optimization problems. Both stochastic and deterministic algorithms have been devised to solve them. The simplest such reconstruction process is the weak string. Exact solutions can be obtained for it and are used to determine the success or failure of the algorithms under precisely controlled conditions. It is concluded that the deterministic algorithm (graduated nonconvexity) outstrips stochastic (simulated annealing) algorithms both in computational efficiency and in problem-solving power.</p>
deterministic algorithms; stochastic algorithms; visual reconstruction; nonconvex optimization; weak string; computational efficiency; problem-solving power; computer vision; computerised picture processing; optimisation

A. Blake, "Comparison of the Efficiency of Deterministic and Stochastic Algorithms for Visual Reconstruction," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 11, no. , pp. 2-12, 1989.
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