Results 21 to 30 of about 73,328 (265)
Bayesian optimization of ESG (Environmental Social Governance) financial investments
Environmental Research Communications, 2023 Financial experts seek to predict the variability of financial markets to ensure investors’ successful investments. However, there has been a big trend in finance in the last few years, which are the ESG (Economic, Social and Governance) criteria, due to
Eduardo C Garrido-Merchán +2 more
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Xibei Gongye Daxue Xuebao, 2021 To overcome the complicated engineering model and huge computational cost, a hierarchical design space reduction strategy based approximate high-dimensional optimization(HSRAHO) method is proposed to deal with the high-dimensional expensive black-box ...
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Black-box optimization methods for hypersonic flow problems [PDF]
International Journal of Fluid EngineeringThis review examines the application of black-box optimization methods to hypersonic flow problems, with a particular emphasis on scenarios where computational fluid dynamics (CFD) simulations function as opaque, nontransparent models.
Davood Hoseinzade +2 more
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Black-box optimization with a politician
CoRR, 2016 19 ...
Sébastien Bubeck, Yin Tat Lee
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Chemical Engineering Transactions, 2021 Rigorous black-box simulations are useful to describe complex systems. However, it cannot be directly integrated into mathematical programming models in some algebraic modeling environments because of the lack of symbolic formulation.
Lucas F. Santos +3 more
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Black Box Optimization Benchmarking of the GLOBAL Method [PDF]
Evolutionary Computation, 2012 GLOBAL is a multi-start type stochastic method for bound constrained global optimization problems. Its goal is to find the best local minima that are potentially global. For this reason it involves a combination of sampling, clustering, and local search.
László Pál +3 more
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Attacking Black-Box Image Classifiers With Particle Swarm Optimization
IEEE Access, 2019 In order to better solve the shortcomings of Deep Neural Networks (DNNs) susceptible to adversarial examples, evaluating existing neural network classification performance and increasing training sets to improve the robustness of classification models ...
Quanxin Zhang +3 more
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Surrogate‐based methods for black‐box optimization [PDF]
International Transactions in Operational Research, 2016 AbstractIn this paper, we survey methods that are currently used in black‐box optimization, that is, the kind of problems whose objective functions are very expensive to evaluate and no analytical or derivative information is available. We concentrate on a particular family of methods, in which surrogate (or meta) models are iteratively constructed and
Ky Khac Vu +3 more
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Opening the black boxes in data flow optimization [PDF]
Proceedings of the VLDB Endowment, 2012 Many systems for big data analytics employ a data flow abstraction to define parallel data processing tasks. In this setting, custom operations expressed as user-defined functions are very common. We address the problem of performing data flow optimization at this level of abstraction, where the semantics of operators are not known.
Fabian Hueske +6 more
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Science and Technology of Advanced Materials: Methods, 2023 Materials screening by high-throughput first-principles calculations is a powerful tool for exploring novel materials with preferable properties. Machine learning techniques are expected to accelerate materials screening by constructing surrogate models ...
Akira Takahashi +4 more
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