Results 51 to 60 of about 12,788,874 (304)
Adaptive Importance Sampling in General Mixture Classes [PDF]
, 2008 In this paper, we propose an adaptive algorithm that iteratively updates both the weights and component parameters of a mixture importance sampling density so as to optimise the importance sampling performances, as measured by an entropy criterion.
A. Doucet +18 more
core +7 more sources
Adaptive query-based sampling for distributed IR [PDF]
, 2006 No abstract ...
Azzopardi, L., Baillie, M., Crestani, F.
core +3 more sources
Fast regression of the tritium breeding ratio in fusion reactors
Machine Learning: Science and Technology, 2023 The tritium breeding ratio (TBR) is an essential quantity for the design of modern and next-generation D-T fueled nuclear fusion reactors. Representing the ratio between tritium fuel generated in breeding blankets and fuel consumed during reactor runtime,
P Mánek +5 more
doaj +1 more source
A survey of adaptive sampling and filtering algorithms for the internet of things
Distributed Event-Based Systems, 2020 The Internet of Things (IoT) represents one of the fastest emerging trends in the area of information and communication technology. The main challenge in the IoT is the timely gathering of data streams from potentially millions of sensors. In particular,
Dimitrios Giouroukis +4 more
semanticscholar +1 more source
Adaptive sampling in ecology: Key challenges and future opportunities
Methods in Ecology and EvolutionTraditional ecological monitoring employs fixed designs, which do not vary over the survey duration. Adaptive sampling, whereby the data already collected informs a sampling design which changes over the course of the study, can provide a more optimal ...
P. Henrys +2 more
semanticscholar +1 more source
An Error-Pursuing Adaptive Uncertainty Analysis Method Based on Bayesian Support Vector Regression
Machines, 2023 The Bayesian support vector regression (BSVR) metamodel is widely used in various engineering fields to analyze the uncertainty arising from uncertain parameters.
Sheng-Tong Zhou +4 more
doaj +1 more source
Pushing towards the Limit of Sampling Rate: Adaptive Chasing Sampling
, 2015 Measurement samples are often taken in various monitoring applications. To reduce the sensing cost, it is desirable to achieve better sensing quality while using fewer samples.
Li, Ying, Wang, Xin, Xie, Kun
core +1 more source
Parsimonious adaptive rejection sampling [PDF]
Electronics Letters, 2017 Monte Carlo (MC) methods have become very popular in signal processing during the past decades. The adaptive rejection sampling (ARS) algorithms are well‐known MC techniques which draw efficiently independent samples from univariate target densities. The ARS schemes yield a sequence of proposal functions that converge towards the target, so that the ...
openaire +2 more sources
Locally Adaptive Sampling [PDF]
2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2010 In this paper, we introduce a class of Locally Adaptive Sampling schemes. In this sampling family, time intervals between samples can be computed by using a function of previously taken samples, called a sampling function. Hence, though it is a non-uniform sampling scheme, we do not need to keep sampling times.
Feizi-Khankandi, Soheil +2 more
openaire +2 more sources
An Adaptive Hybrid Sampling Method for Free-Form Surfaces Based on Geodesic Distance
Sensors, 2023 High precision geometric measurement of free-form surfaces has become the key to high-performance manufacturing in the manufacturing industry. By designing a reasonable sampling plan, the economic measurement of free-form surfaces can be realized.
Chen Chen +5 more
doaj +1 more source