Results 21 to 30 of about 893,007 (263)
Variance Reduction of Sequential Monte Carlo Approach for GNSS Phase Bias Estimation
Mathematics, 2020 Global navigation satellite systems (GNSS) are an important tool for positioning, navigation, and timing (PNT) services. The fast and high-precision GNSS data processing relies on reliable integer ambiguity fixing, whose performance depends on phase bias
Yumiao Tian, Maorong Ge, Frank Neitzel
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Semi-Stochastic Gradient Descent Methods
Frontiers in Applied Mathematics and Statistics, 2017 In this paper we study the problem of minimizing the average of a large number of smooth convex loss functions. We propose a new method, S2GD (Semi-Stochastic Gradient Descent), which runs for one or several epochs in each of which a single full gradient
Jakub Konečný, Peter Richtárik
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Integrated Variance Reduction Strategies [PDF]
Proceedings of 1993 Winter Simulation Conference - (WSC '93), 1993 In this paper we develop strategies for integrating certain well-known variance reduction techniques to estimate a mean response in a finite-horizon simulation experiment. Our building blocks are the techniques of conditional expectation, correlation induction, and control variates.
Athanassios N. Avramidis +1 more
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Mathematics, 2023 Monte Carlo simulation is performed with uniformly distributed U(0,1) pseudo-random numbers. Because the numbers are generated from a mathematical formula, they will contain some serial correlation, even if very small.
Dennis Ridley, Pierre Ngnepieba
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Implementation of variance reduction techniques applied to the pricing of investment certificates [PDF]
Risk Management Magazine, 2023 Certificates are structured financial instruments that aim to provide investors with investment solutions tailored to their needs. Certificates can be modeled using a bond component and a derivative component, typically an options strategy.
Anna Bottasso +3 more
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Variance reduction and cluster decomposition [PDF]
Physical Review D, 2018 It is a common problem in lattice QCD calculation of the mass of the hadron with an annihilation channel that the signal falls off in time while the noise remains constant. In addition, the disconnected insertion calculation of the three-point function and the calculation of the neutron electric dipole moment with the $θ$ term suffer from a noise ...
Liu, Keh-Fei, Liang, Jian, Yang, Yi-Bo
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Variance reduction for Metropolis–Hastings samplers
Statistics and Computing, 2022 AbstractWe introduce a general framework that constructs estimators with reduced variance for random walk Metropolis and Metropolis-adjusted Langevin algorithms. The resulting estimators require negligible computational cost and are derived in a post-process manner utilising all proposal values of the Metropolis algorithms.
Angelos Alexopoulos +2 more
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A Neutrosophic Monte Carlo Framework for Modeling Indeterminate Participation and Cultural Impact in Tourism Service Quality of Ethnic Sports Events [PDF]
Neutrosophic Sets and SystemsEthnic sports tourism involves complex cultural, social, and economic interactions, where uncertainty arises not only from randomness but also from incomplete and contradictory information. Classical probability models cannot fully capture these features.
Chaolumen Ge, Xuelian Liu
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Stochastic Recursive Gradient Support Pursuit and Its Sparse Representation Applications
Sensors, 2020 In recent years, a series of matching pursuit and hard thresholding algorithms have been proposed to solve the sparse representation problem with ℓ0-norm constraint.
Fanhua Shang +5 more
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Stress-weighted spatial averaging of random fields in geotechnical risk assessment
Studia Geotechnica et Mechanica, 2021 Effects of spatial fluctuations of soil parameters are considered in a new context – considering variability of soil parameters in conjunction with non-uniform stress fields, which can locally amplify (or suppress) subsoil inhomogeneities.
Brząkała Włodzimierz
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