Results 11 to 20 of about 183,644 (280)
Gibbs-Slice Sampling Algorithm for Estimating the Four-Parameter Logistic Model
Frontiers in Psychology, 2020 The four-parameter logistic (4PL) model has recently attracted much interest in educational testing and psychological measurement. This paper develops a new Gibbs-slice sampling algorithm for estimating the 4PL model parameters in a fully Bayesian ...
Jiwei Zhang +5 more
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A Dirichlet Process Prior Approach for Covariate Selection
Entropy, 2020 The variable selection problem in general, and specifically for the ordinary linear regression model, is considered in the setup in which the number of covariates is large enough to prevent the exploration of all possible models.
Stefano Cabras
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Topical Text Network Construction Method Based on Gibbs Sampling Results [PDF]
Jisuanji gongcheng, 2017 Mining the probability distribution of topic words in document collection can make a summary understanding of the document content.Further exploring the connection relationship between words in a given topic not only riches the meaning of topic words,but
ZHANG Zhiyuan,YANG Hongjing,ZHAO Yue
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Journal of Machine Learning Research, 2013 The Gibbs sampler is one of the most popular algorithms for inference in statistical models. In this paper, we introduce a herding variant of this algorithm, called herded Gibbs, that is entirely deterministic. We prove that herded Gibbs has an $O(1/T)$ convergence rate for models with independent variables and for fully connected probabilistic ...
Bornn, L. +5 more
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Productioon uncertainties modelling by Bayesian inference using Gibbs sampling
South African Journal of Industrial Engineering, 2015 Analysis by modelling production throughput is an efficient way to provide information for production decision-making. Observation and investigation based on a real-life tile production line revealed that the five main uncertain variables are demand rate,
Azizi, Amir +3 more
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Fast Gibbs sampling for high-dimensional Bayesian inversion [PDF]
, 2016 Solving ill-posed inverse problems by Bayesian inference has recently attracted considerable attention. Compared to deterministic approaches, the probabilistic representation of the solution by the posterior distribution can be exploited to explore and ...
Burger M +15 more
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Fast algorithms for band-limited extrapolation by over sampling and Fourier series
EURASIP Journal on Advances in Signal Processing, 2023 In this paper, fast algorithms for the extrapolation of band-limited signals are presented by the sampling theorem and Fourier series in the case of over sampling. Assume the band-limited signal is known in a finite interval. We update the signal outside
Weidong Chen
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PhyloGibbs: a Gibbs sampling motif finder that incorporates phylogeny.
PLoS Computational Biology, 2005 A central problem in the bioinformatics of gene regulation is to find the binding sites for regulatory proteins. One of the most promising approaches toward identifying these short and fuzzy sequence patterns is the comparative analysis of orthologous ...
Rahul Siddharthan +2 more
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Gibbs Sampling Subjectively Interesting Tiles [PDF]
, 2020 The local pattern mining literature has long struggled with the so-called pattern explosion problem: the size of the set of patterns found exceeds the size of the original data. This causes computational problems (enumerating a large set of patterns will inevitably take a substantial amount of time) as well as problems for interpretation and usability (
Bendimerad, Anes +4 more
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