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Global Search versus Local Search in Hyperparameter Optimization
2022 IEEE Congress on Evolutionary Computation (CEC), 2022Yoshihiko Ozaki +2 more
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Multiple Parallel Local Searches in Global Optimization
2000The unconstrained global programming problem is addressed using an efficient multi-start algorithm, in which parallel local searches contribute towards a Bayesian global stopping criterion. The stopping criterion, denoted the unified Bayesian global stopping criterion, is based on the mild assumption that the probability of convergence to the global
Hermanus P. J. Bolton +2 more
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Thompson Sampling for Optimizing Stochastic Local Search
2017Stochastic local search (SLS), like many other stochastic optimization algorithms, has several parameters that need to be optimized in order for the algorithm to find high quality solutions within a short amount of time. In this paper, we formulate a stochastic local search bandit (\(\mathtt{SLSB}\)), which is a novel learning variant of SLS based on ...
Tong Yu 0001 +2 more
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Locally Optimized Hashing for Nearest Neighbor Search
2015Fast nearest neighbor search (NNS) is becoming important to utilize massive data. Recent work shows that hash learning is effective for NNS in terms of computational time and space. Existing hash learning methods try to convert neighboring samples to similar binary codes, and their hash functions are globally optimized on the data manifold.
Seiya Tokui +2 more
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Chaotic Local Search-Based Differential Evolution Algorithms for Optimization
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021Shangce Gao, Yang Yu, Yirui Wang
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A Two-Stage Swarm Optimizer With Local Search for Water Distribution Network Optimization
IEEE Transactions on Cybernetics, 2023Ya-Hui Jia, Yi Mei, Mengjie Zhang
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IEEE Transactions on Emerging Topics in Computational Intelligence, 2023
Zi-Jia Wang, Zhi-Hui Zhan, Yun Li
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Zi-Jia Wang, Zhi-Hui Zhan, Yun Li
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