DisSAGD: A Distributed Parameter Update Scheme Based on Variance Reduction [PDF]
Sensors, 2021 Machine learning models often converge slowly and are unstable due to the significant variance of random data when using a sample estimate gradient in SGD.
Haijie Pan, Lirong Zheng
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Some variance reduction methods for numerical stochastic homogenization. [PDF]
Philos Trans A Math Phys Eng Sci, 2016 We overview a series of recent works devoted to variance reduction techniques for numerical stochastic homogenization. Numerical homogenization requires solving a set of problems at the micro scale, the so-called corrector problems.
Blanc X, Le Bris C, Legoll F.
europepmc +4 more sources
Fast PET reconstruction with variance reduction and prior-aware preconditioning [PDF]
Frontiers in Nuclear MedicineWe investigated subset-based optimization methods for positron emission tomography (PET) image reconstruction incorporating a regularizing prior. PET reconstruction methods that use a prior, such as the relative difference prior (RDP), are of particular ...
Matthias J. Ehrhardt +2 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.
Liang, Jian, Liu, Keh-Fei, Yang, Yi-Bo
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Accelerated Stochastic Variance Reduction Gradient Algorithms for Robust Subspace Clustering [PDF]
SensorsRobust face clustering enjoys a wide range of applications for gate passes, surveillance systems and security analysis in embedded sensors. Nevertheless, existing algorithms have limitations in finding accurate clusters when data contain noise (e.g ...
Hongying Liu +5 more
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Optimization of variance reduction techniques used in EGSnrc Monte Carlo Codes [PDF]
Journal of Medical Physics, 2018 Monte Carlo (MC) simulations are often used in calculations of radiation transport to enable accurate prediction of radiation-dose, even though the computation is relatively time-consuming.
Sangeetha Shanmugasundaram +1 more
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Variance Reduction Using Nonreversible Langevin Samplers. [PDF]
J Stat Phys, 2016 A standard approach to computing expectations with respect to a given target measure is to introduce an overdamped Langevin equation which is reversible with respect to the target distribution, and to approximate the expectation by a time-averaging estimator.
Duncan AB, Lelièvre T, Pavliotis GA.
europepmc +7 more sources
Effects of yoga practice on acumeridian energies: Variance reduction implies benefits for regulation [PDF]
International Journal of Yoga, 2013 Background and Objective: This paper concerns mechanisms responsible for the efficacy of yoga medicine, traditionally attributed to the enlivenment of prana.
Niharika Nagilla +2 more
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ANALYSIS OF DOSE RATES AROUND THE SLOVENIAN SILO-TYPE LILW REPOSITORY USING ADVANTG [PDF]
EPJ Web of Conferences, 2021 The ADVANTG code was used to analyze dose rates from the proposed Slovenian silo-type low and intermediate level waste (LILW) repository. Detailed calculations of dose rates are challenging as gamma-sources are located in thick concrete containers and ...
Kotnik Domen +3 more
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EFFECT OF THE UNIFORM FISSION SOURCE METHOD ON LOCAL POWER VARIANCE IN FULL CORE SERPENT CALCULATION [PDF]
EPJ Web of Conferences, 2021 One of challenges of the Monte Carlo full core simulations is to obtain acceptable statistical variance of local parameters throughout the whole reactor core at a reasonable computation cost.
Bilodid Yurii, Leppänen Jaakko
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