Results 11 to 20 of about 914,252 (305)

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
doaj   +2 more sources

Fast PET reconstruction with variance reduction and prior-aware preconditioning [PDF]

Frontiers in Nuclear Medicine
We 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, Zeljko Kereta, Georg Schramm   +2 more
doaj   +2 more sources

L2 Model Reduction and Variance Reduction

IFAC Proceedings Volumes, 1999
In this contribution we demonstrate that estimating a low order model (leaving some dynamics unmodeled) by L2 model reduction of a higher order estimated model may give smaller variance and mean square error than directly estimating it from the same data
Ljung, Lennart, Fredrik Tjärnström, Lennart Ljung, Tjärnström, Fredrik   +3 more
core   +4 more sources

Accelerated Stochastic Variance Reduction Gradient Algorithms for Robust Subspace Clustering [PDF]

Sensors
Robust 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, Linlin Yang, Longge Zhang, Fanhua Shang, Yuanyuan Liu, Lijun Wang   +5 more
doaj   +2 more sources

Variance Reduction in Smoothing Splines

Scandinavian Journal of Statistics, 2009
We develop a variance reduction method for smoothing splines. For a given point of estimation, we define a variance-reduced spline estimate as a linear combination of classical spline estimates at three nearby points.
Paige, Robert, L., Wang, Keyi, Sun, Shan, ROBERT L. PAIGE, SHAN SUN, KEYI WANG   +5 more
core   +3 more sources

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, Sureka Chandrasekaran   +1 more
doaj   +2 more sources

Variance reduction for Metropolis–Hastings samplers

Statistics and Computing, 2023
We introduce a general framework that constructs estimators with reduced variance for random walk Metropolis and Metropolis-adjusted Langevin algorithms.
Angelos Alexopoulos, Petros Dellaportas, Michalis K. Titsias   +2 more
core   +5 more sources

Variance Reduction

, 2017
Increased computer speed and memory have encouraged simulation analysts to develop ever more realistic stochastic models. Despite these advancements in computing hardware, the most significant gains in the speed of stochastic simulation are still the ...
Ridder, A.A.N., Ad Ridder, Zdravko Botev, Ridder, A.A.N.; id_orcid, Ridder, A, Botev, Z ; https://orcid.org/, Botev, Z.I.   +6 more
core   +4 more sources

Integrated variance reduction strategies for simulation

Operations Research, 1996
We develop strategies for integrated use of certain well-known variance reduction techniques to estimate a mean response in a finite-horizon simulation experiment.
Athanassios N. Avramidis, Avramidis, Athanassios.N., James R. Wilson, Wilson, James R.   +3 more
core   +3 more sources

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
doaj   +1 more source