Results 1 to 10 of about 3,977,371 (295)
Nyquist Sampling Conditions of Some Diffraction Algorithms with Adjustable Magnification
Sensors, 2023 Diffraction algorithms with adjustable magnification are dominant in holographic projection and imaging. However, the algorithms are limited by the Nyquist sampling conditions, and simulation results with inappropriate parameters sometimes appear with ...
Chunzheng Wang +3 more
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Application and comparison of several adaptive sampling algorithms in reduced order modeling [PDF]
HeliyonModel Order Reduction (MOR) techniques have extensive applications across scientific and engineering disciplines, such as neutron field reconstruction of nuclear reactor cores, thermoelastic field reconstruction, fluid, and solid mechanics.
Xirui Liu +3 more
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A Comparison of Existing Bootstrap Algorithms for Multi-Stage Sampling Designs
Stats, 2022 Multi-stage sampling designs are often used in household surveys because a sampling frame of elements may not be available or for cost considerations when data collection involves face-to-face interviews. In this context, variance estimation is a complex
Sixia Chen +2 more
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Estimation of Distribution Algorithms with Fuzzy Sampling for Stochastic Programming Problems
Applied Sciences, 2020 Generating practical methods for simulation-based optimization has attracted a great deal of attention recently. In this paper, the estimation of distribution algorithms are used to solve nonlinear continuous optimization problems that contain noise. One
Abdel-Rahman Hedar +2 more
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Sampling Algorithms and Coresets for $\ell_p$ Regression
SIAM Journal on Computing, 2009 19 pages, 1 ...
Michael Mahoney, Petros Drineas
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A statistical test for Nested Sampling algorithms [PDF]
Statistics and Computing, 2014 11 pages, 7 figures.
Johannes Büchner
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A Proximal Algorithm for Sampling
Trans. Mach. Learn. Res., 2022 25 ...
Jiaming Liang, Yongxin Chen
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Algorithms for the Communication of Samples
CoRR, 2021 The efficient communication of noisy data has applications in several areas of machine learning, such as neural compression or differential privacy, and is also known as reverse channel coding or the channel simulation problem. Here we propose two new coding schemes with practical advantages over existing approaches.
Lucas Theis, Noureldin Y. Ahmed
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A Comparative Study for Different Resampling Techniques for Imbalanced datasets [PDF]
IJCI International Journal of Computers and Information, 2023 The imbalanced data is a significant challenge forresearchers in supervised machine learning. Current data mining algorithms are not effective for processing imbalanced data.In fact, this problem reduces classification accuracy because theprediction of ...
Alaa Elsobky +2 more
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A latent slice sampling algorithm
Computational Statistics & Data Analysis, 2023 19 pages, 10 ...
Yanxin Li, Stephen G. Walker
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