Results 31 to 40 of about 226,052 (275)
IEEE Open Journal of the Computer Society, 2020 Widely deployed smart cameras are generating a large amount of video data and capable of processing frames on devices. Empowered by edge computing, the video data can also be offloaded to edge servers for processing.
Yang Deng, Tao Han, Nirwan Ansari
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Neural-BO: A Black-box Optimization Algorithm using Deep Neural Networks [PDF]
Neurocomputing, 2023 Bayesian Optimization (BO) is an effective approach for global optimization of black-box functions when function evaluations are expensive. Most prior works use Gaussian processes to model the black-box function, however, the use of kernels in Gaussian ...
Dat Phan-Trong +2 more
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On the Design of a Class of Rotary Compressors Using Bayesian Optimization
Machines, 2021 The optimization process of compressors is usually regarded as a ‘black-box’ problem, in which the mathematical form underlying the relationship between design parameters and the design objective is impractical and costly to be obtained.
Kui Lu +2 more
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Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms [PDF]
Annual Conference on Genetic and Evolutionary Computation, 2023 The L∞ star discrepancy is a measure for the regularity of a finite set of points taken from [0, 1)d. Low discrepancy point sets are highly relevant for Quasi-Monte Carlo methods in numerical integration and several other applications.
F. Clément +5 more
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OpenBox: A Generalized Black-box Optimization Service [PDF]
Knowledge Discovery and Data Mining, 2021 Black-box optimization (BBO) has a broad range of applications, including automatic machine learning, engineering, physics, and experimental design. However, it remains a challenge for users to apply BBO methods to their problems at hand with existing ...
Yang Li +11 more
semanticscholar +1 more source
Adaptive divergence for rapid adversarial optimization [PDF]
PeerJ Computer Science, 2020 Adversarial Optimization provides a reliable, practical way to match two implicitly defined distributions, one of which is typically represented by a sample of real data, and the other is represented by a parameterized generator.
Maxim Borisyak +2 more
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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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Functionality-Preserving Black-Box Optimization of Adversarial Windows Malware [PDF]
IEEE Transactions on Information Forensics and Security, 2020 Windows malware detectors based on machine learning are vulnerable to adversarial examples, even if the attacker is only given black-box query access to the model.
Luca Demetrio +4 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 for integer-variable problems using Ising machines and factorization machines [PDF]
arXiv.org, 2022 Black-box optimization has potential in numerous applications such as hyperparameter optimization in machine learning and optimization in design of experiments.
Yuya Seki, R. Tamura, Shu Tanaka
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