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Efficient Hyperparameter Optimization of Deep Learning Algorithms Using Deterministic RBF Surrogates

, , , and . (2016)

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Efficient Hyperparameter Optimization for Deep Learning Algorithms Using Deterministic RBF Surrogates., , , and . AAAI, page 822-829. AAAI Press, (2017)Multi objective optimization of computationally expensive multi-modal functions with RBF surrogates and multi-rule selection., and . J. Glob. Optim., 64 (1): 17-32 (2016)Integrating ε-dominance and RBF surrogate optimization for solving computationally expensive many-objective optimization problems., , and . J. Glob. Optim., 82 (4): 965-992 (2022)Hyperparameter Optimization of Deep Neural Networks Using Non-Probabilistic RBF Surrogate Model., , , and . CoRR, (2016)Efficient Multi-Objective Optimization through Population-based Parallel Surrogate Search., and . CoRR, (2019)SOP: parallel surrogate global optimization with Pareto center selection for computationally expensive single objective problems., , and . J. Glob. Optim., 66 (3): 417-437 (2016)Surrogate Many Objective Optimization: Combining Evolutionary Search, -Dominance and Connected Restarts., , and . WCGO, volume 991 of Advances in Intelligent Systems and Computing, page 681-690. Springer, (2019)Efficient Hyperparameter Optimization of Deep Learning Algorithms Using Deterministic RBF Surrogates, , , and . (2016)Efficient parallel surrogate optimization algorithm and framework with application to parameter calibration of computationally expensive three-dimensional hydrodynamic lake PDE models., , , and . Environ. Model. Softw., (2021)SOP-Hybrid: A Parallel Surrogate-Based Candidate Search Algorithm for Expensive Optimization on Large Parallel Clusters., and . WCGO, volume 991 of Advances in Intelligent Systems and Computing, page 672-680. Springer, (2019)