Results 31 to 40 of about 2,159,110 (277)
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
doaj +1 more source
IEEE Access, 2020 The power consumption at the receiver side will be dramatically increased in the millimetre-wave and massive multiple-input-multiple-output (MIMO) communication systems due to the wide bandwidth and a large number of antennas adopted.
Yi Gong +3 more
doaj +1 more source
An Integral-Equation-Based Variance Reduction Method for Accelerated Monte Carlo Simulations
Photonics, 2023 In this work, we introduce a novel variance reduction approach utilising the integral formulation of the radiative transfer equation to calculate the radiance in a planar symmetric slab geometry.
David Hevisov +3 more
doaj +1 more source
Robust Support Vector Machine Based on Momentum Acceleration Zero-Order Variance Reduction [PDF]
Jisuanji gongcheng, 2020 In the actual classification problem,there is often a certain amount of noise in the data caused by the influence of artificial or other factors,so it is very important to improve the anti-noise ability of the classifier.However,the hinge loss function ...
LU Shuxia, CAI Lianxiang, ZHANG Luohuan
doaj +1 more source
Momentum-Based Variance Reduction in Non-Convex SGD [PDF]
, 2019 Variance reduction has emerged in recent years as a strong competitor to stochastic gradient descent in non-convex problems, providing the first algorithms to improve upon the converge rate of stochastic gradient descent for finding first-order critical ...
Cutkosky, Ashok, Orabona, Francesco
core +1 more source
Variance-Reduction Methods for Monte Carlo Simulation of Radiation Transport
Frontiers in Physics, 2021 After a brief description of the essentials of Monte Carlo simulation methods and the definition of simulation efficiency, the rationale for variance-reduction techniques is presented.
Salvador García-Pareja +2 more
doaj +1 more source
L 2 Model Reduction and Variance Reduction
IFAC Proceedings Volumes, 2000 The authors study several variance properties related to model reduction for finite impulse response (FIR) and output error (OE) models. The variances of two models, one deduced directly from data and the other by reducing a high order model by \(L_2\) model reduction, are compared.
Tjärnström, F., Ljung, L.
openaire +3 more sources
Stochastic Variance Reduced Primal–Dual Hybrid Gradient Methods for Saddle-Point Problems
MathematicsRecently, many stochastic Alternating Direction Methods of Multipliers (ADMMs) have been proposed to solve large-scale machine learning problems. However, for large-scale saddle-point problems, the state-of-the-art (SOTA) stochastic ADMMs still have high
Weixin An +3 more
doaj +1 more source
Test Results of Variance Reduction Techniques Applied to Deep Penetration Problem
Глобальная ядерная безопасность, 2022 Nowadays, there is a problem of a lack of computer power to conduct high-precision reactor analysis. There are several factors that increase the excessive computational load and make it difficult to calculate nuclear reactor full-scale models using Monte
E. V. Bogdanova, G. V. Tikhomirov
doaj +1 more source
Variance reduction for discretised diffusions via regression
, 2017 In this paper we present a novel approach towards variance reduction for discretised diffusion processes. The proposed approach involves specially constructed control variates and allows for a significant reduction in the variance for the terminal ...
Belomestny, Denis +3 more
core +1 more source