Results 21 to 30 of about 3,977,371 (295)
Practical Algorithms for On-Line Sampling [PDF]
, 1998 To appear in the Proc.
Domingo Soriano, Carlos +2 more
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Estimating truncation effects of quantum bosonic systems using sampling algorithms
Machine Learning: Science and Technology, 2023 To simulate bosons on a qubit- or qudit-based quantum computer, one has to regularize the theory by truncating infinite-dimensional local Hilbert spaces to finite dimensions.
Masanori Hanada +3 more
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Designing algorithms by sampling
Discrete Applied Mathematics, 2001 AbstractThis paper describes a method for empirical algorithm design, called database learning, using which an algorithm is constructed based on the solutions produced by an oracle on instances from a given input domain. We present experimental results of applying the strategy to designing heuristics for the problem of constructing a maximum ...
Mark K. Goldberg, David L. Hollinger
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Land, 2021 Data driven methods are widely used for the development of Landslide Susceptibility Mapping (LSM). The results of these methods are sensitive to different factors, such as the quality of input data, choice of algorithm, sampling strategies, and data ...
Minu Treesa Abraham +4 more
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Importance Sampling for Objetive Funtion Estimations in Neural Detector Traing Driven by Genetic Algorithms [PDF]
, 2010 To train Neural Networks (NNs) in a supervised way, estimations of an objective function must be carried out. The value of this function decreases as the training progresses and so, the number of test observations necessary for an accurate estimation has
Raúl Vicen-Bueno +9 more
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Quantitative estimation of sampling uncertainties for mycotoxins in cereal shipments [PDF]
, 2012 Many countries receive shipments of bulk cereals from primary producers. There is a volume of work that is ongoing that seeks to arrive at appropriate standards for the quality of the shipments and the means to assess the shipments as they are out-loaded.
Bourgeois, Florent +2 more
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An Algorithm to Sample an Anatomy With Uncertainty
Computing in Cardiology Conference (CinC), 2018 Image artefact, resolution and contrast all impact our ability to quantify anatomy. In the context of patient-specific simulations this uncertainty in shape can lead to uncertainty in model predictions. We propose and apply a method for quantifying uncertainty in shape and demonstrate the impact of uncertain shape on activation time predictions in a ...
Corrado, C. +8 more
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An Algorithm for Unbiased Random Sampling [PDF]
The Computer Journal, 1982 The problem of random sampling occurs in many different contexts. For example, we may wish to study experimentally the behaviour of a new data structure for searching. Then the easiest way is to generate a set of data elements, construct the corresponding structure and then perform searching of some elements belonging (or not belonging) to the data ...
Jarmo Ernvall, Olli Nevalainen
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Likelihood inflating sampling algorithm [PDF]
Canadian Journal of Statistics, 2017 AbstractMarkov Chain Monte Carlo (MCMC) sampling from a posterior distribution corresponding to a massive data set can be computationally prohibitive as producing one sample requires a number of operations that is linear in the data size. In this article we introduce a new communication‐free parallel method, the “Likelihood Inflating Sampling Algorithm
Reihaneh Entezari +2 more
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Machine Learning Algorithms Based on Sampling Techniques for Raisin Grains Classification
JOIV: International Journal on Informatics Visualization, 2023 Raisin grains are among the agricultural commodities that can benefit health. The production of raisin grains needs to be classified to achieve optimal results.
Achmad Bisri, Mustafa Man
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