Results 51 to 60 of about 226,052 (275)
Fast Black-Box Quantum State Preparation [PDF]
Quantum, 2022 Quantum state preparation is an important ingredient for other higher-level quantum algorithms, such as Hamiltonian simulation, or for loading distributions into a quantum device to be used e.g.
Johannes Bausch
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Black-Box Audio Adversarial Attack Using Particle Swarm Optimization
IEEE Access, 2022 The development of artificial neural networks and artificial intelligence has helped to address problems and improve services in various fields, such as autonomous driving, image classification, medical diagnosis, and speech recognition.
Hyunjun Mun +3 more
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Using the Empirical Attainment Function for Analyzing Single-Objective Black-Box Optimization Algorithms [PDF]
IEEE Transactions on Evolutionary ComputationA widely accepted way to assess the performance of iterative black-box optimizers is to analyze their empirical cumulative distribution function (ECDF) of predefined quality targets achieved not later than a given runtime.
Manuel L'opez-Ib'anez +3 more
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Variational quantum algorithm for unconstrained black box binary optimization: Application to feature selection [PDF]
Quantum, 2023 We introduce a variational quantum algorithm to solve unconstrained black box binary optimization problems, i.e., problems in which the objective function is given as black box.
Christa Zoufal +8 more
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Efficient Robot Design With Multi-Objective Black-Box Optimization and Large Language Models
IEEE AccessVarious methods for robot design optimization have been developed so far. These methods are diverse, ranging from numerical optimization to black-box optimization.
Kento Kawaharazuka +4 more
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Applied Sciences, 2021 Biogas production is a relevant component in renewable energy systems. The paper addresses modeling approaches from an energy system, as well as from a process optimization, point of view.
Mathias Heiker +4 more
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DiBB: distributing black-box optimization
Annual Conference on Genetic and Evolutionary Computation, 2022 DiBB (for Distributing Black-Box) is a meta-algorithm and framework that addresses the decades-old scalability issue of Black-Box Optimization (BBO), including Evolutionary Computation.
Giuseppe Cuccu +4 more
semanticscholar +1 more source
Kriging-based optimization design for a new style shell with black box constraints
Journal of Algorithms & Computational Technology, 2017 Complex engineering applications generally have the black box and computationally expensive characteristics. Surrogate-based optimization algorithms can effectively solve expensive black box optimization problems. This paper employs the kriging predictor
Huachao Dong, Baowei Song, Peng Wang
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Continuous black-box optimization with an Ising machine and random subspace coding
Physical Review Research, 2022 A black-box optimization algorithm such as Bayesian optimization finds the extremum of an unknown function by alternating the inference of the underlying function and optimization of an acquisition function.
Syun Izawa +4 more
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Evolutionary Black-Box Topology Optimization: Challenges and Promises [PDF]
IEEE Transactions on Evolutionary Computation, 2020 Black-box topology optimization (BBTO) uses evolutionary algorithms and other soft computing techniques to generate near-optimal topologies of mechanical structures. Although evolutionary algorithms are widely used to compensate the limited applicability of conventional gradient optimization techniques, methods based on BBTO have been criticized due to
David Guirguis +10 more
openaire +2 more sources