IEEE Access, 2019 Multi-modal optimization is a troublesome problem faced by optimization algorithms. The multiscale quantum harmonic oscillator algorithm (MQHOA) utilizes group statistics strategy to evaluate the state of the population and neglects the individual state.
Bo Li, Peng Wang, Jin Jin
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Using Parameter Elimination to Solve Discrete Linear Chebyshev Approximation Problems
Mathematics, 2020 We consider discrete linear Chebyshev approximation problems in which the unknown parameters of linear function are fitted by minimizing the least maximum absolute deviation of errors.
Nikolai Krivulin
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Deep Sparse Learning for Automatic Modulation Classification Using Recurrent Neural Networks
Sensors, 2021 Deep learning models, especially recurrent neural networks (RNNs), have been successfully applied to automatic modulation classification (AMC) problems recently.
Ke Zang, Wenqi Wu, Wei Luo
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Multivariate Specification Tests Based on a Dynamic Rosenblatt Transform
, 2018 This paper considers parametric model adequacy tests for nonlinear multivariate dynamic models. It is shown that commonly used Kolmogorov-type tests do not take into account cross-sectional nor time-dependence structure, and a test, based on multi ...
Kheifets, Igor L.
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Optimal computational and statistical rates of convergence for sparse nonconvex learning problems [PDF]
, 2013 We provide theoretical analysis of the statistical and computational properties of penalized $M$-estimators that can be formulated as the solution to a possibly nonconvex optimization problem.
Liu, Han, Wang, Zhaoran, Zhang, Tong
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Optimal hog cell to image ratio for robust multi-sensor face recognition systems [PDF]
Serbian Journal of Electrical Engineering, 2019 The main problem for modern visible light face recognition has been accurate identification under variable environmental conditions. Thermal infrared facial images utilization in face recognition systems can provide a solution for problems ...
Pavlović Miloš +4 more
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Deep learning-based self-induced emotion recognition using EEG
Frontiers in Neuroscience, 2022 Emotion recognition from electroencephalogram (EEG) signals requires accurate and efficient signal processing and feature extraction. Deep learning technology has enabled the automatic extraction of raw EEG signal features that contribute to classifying ...
Yerim Ji, Suh-Yeon Dong
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A Review of automatic differentiation and its efficient implementation
, 2019 Derivatives play a critical role in computational statistics, examples being Bayesian inference using Hamiltonian Monte Carlo sampling and the training of neural networks.
Margossian, Charles C.
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Computational Approach Test using Likelihood Based Tests for the Equality of Inverse Gaussian Means
Revstat Statistical JournalIn this study, we propose three different test procedures by plugging the Wald (W), score (S) and likelihood ratio (LR) statistics into the computational approach test (CAT) to test the equality of inverse Gaussian means when the scale parameters are ...
Gamze Güven +2 more
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Coding Environment and Exploration Curriculum for Max-Min Optimizations with an Evolution Strategy
Journal of Educational Research in Mathematics, 2021 The purpose of this study is to develop a curriculum of school mathematics and artificial intelligence regarding max-min problems. We also developed a coding environment for a designed curriculum that can be accessed and utilized at codingmath.org ...
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