Abstract
In the present paper, we present a multi-start method with dynamic cutting of “unpromising” starts of locally optimal algorithms for solving continuous unconditional optimization problems. We also describe our results of testing of the proposed method for solving problems of feed-forward neural network training.
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The work was done with the financial support of RBRF (grant no. 19-07-00614).
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Kostenko, V.A. Multi-Start Method with Cutting for Solving Problems of Unconditional Optimization. Opt. Mem. Neural Networks 29, 30–36 (2020). https://doi.org/10.3103/S1060992X20010099
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DOI: https://doi.org/10.3103/S1060992X20010099