has been cited by the following article(s):
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Cumulative Regret Analysis of the Piyavskii–Shubert Algorithm and Its Variants for Global Optimization
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Proceedings of the AAAI Conference on …,
2024 |
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[2]
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A mixed algorithm for smooth global optimization
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Madani - Journal of Mathematical Modeling,
2023 |
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[3]
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Efficient Lipschitzian Global Optimization of H\" older Continuous Multivariate Functions
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arXiv preprint arXiv:2303.14293,
2023 |
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[4]
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Low regret binary sampling method for efficient global optimization of univariate functions
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arXiv preprint arXiv:2201.07164,
2022 |
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[5]
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to : A Meta Algorithm for Multivariate Global Optimization via Univariate Optimizers
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arXiv preprint arXiv:2209.03246,
2022 |
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[6]
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Efficient Minimax Optimal Global Optimization of Lipschitz Continuous Multivariate Functions
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arXiv preprint arXiv:2206.02383,
2022 |
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[7]
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Regret analysis of global optimization in univariate functions with lipschitz derivatives
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arXiv preprint arXiv:2108.10859,
2021 |
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[8]
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ALGORITHMS, LEARNING, AND OPTIMIZATION
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2020 |
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[9]
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Regret analysis of the Piyavskii-Shubert algorithm for global Lipschitz optimization
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2020 |
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[10]
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A deterministic method for continuous global optimization using a dense curve
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2020 |
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[11]
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Améliorations de certaines méthodes probabilistes en optimisation globale
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2018 |
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[12]
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Continuous global optimization through the generation of parametric curves
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Applied Mathematics and Computation,
2016 |
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[13]
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Leap Gradient Algorithm
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arXiv preprint arXiv:1405.5548,
2014 |
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[14]
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Leap Gradient Algorithm The Fastest Method for Univariate Polynomial Extrema
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2014 |
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[1]
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A deterministic method for continuous global optimization using a dense curve
Mathematics and Computers in Simulation,
2020
DOI:10.1016/j.matcom.2020.05.029
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[2]
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Continuous global optimization through the generation of parametric curves
Applied Mathematics and Computation,
2016
DOI:10.1016/j.amc.2016.01.067
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