Results 1 to 10 of about 758 (67)
Prior Distribution and Entropy in Computer Adaptive Testing Ability Estimation through MAP or EAP
Entropy, 2022 To derive a latent trait (for instance ability) in a computer adaptive testing (CAT) framework, the obtained results from a model must have a direct relationship to the examinees’ response to a set of items presented.
Joel Suárez-Cansino +4 more
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Constrained Adjusted Maximum a Posteriori Estimation of Bayesian Network Parameters
Entropy, 2021 Maximum a posteriori estimation (MAP) with Dirichlet prior has been shown to be effective in improving the parameter learning of Bayesian networks when the available data are insufficient.
Ruohai Di +3 more
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Few‐shot classification using Gaussianisation prototypical classifier
IET Computer Vision, 2023 Few‐shot classification (FSC) aims at classifying query samples into correct classes given only a few labelled samples. Prototypical Classifier (PC) can be chosen to be an ideal classifier for settling this problem, as it has good properties of low ...
Fan Liu, Feifan Li, Sai Yang
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Multiframe maximum a posteriori estimators for single‐microphone speech enhancement
IET Signal Processing, 2021 Multiframe maximum a posteriori (MAP) estimators are applied to a single‐microphone noise reduction problem. Several attempts have been made to exploit the interframe correlation (IFC) between speech coefficients in the short‐time Fourier transform ...
Raziyeh Ranjbaryan, Hamid Reza Abutalebi
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Foundation of 2-Symbolic Plithogenic Maximum a Posteriori Estimation [PDF]
Neutrosophic Sets and Systems, 2023 In this paper, we introduce and define for the first time the plithogenic loss function, plithogenic risk function, plithogenic maximum likelihood function, and plithogenic posterior risk function, which form a base to easily define the plithogenic ...
Nizar Altounji +2 more
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IEEE Access, 2022 Introducing parameter constraints has become a mainstream approach for learning Bayesian network parameters with small datasets. The QMAP (Qualitative Maximum a Posteriori) estimation has produced the best learning accuracy among existing learning ...
Ruohai Di +3 more
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Dynamic PET Image Reconstruction Incorporating Multiscale Superpixel Clusters
IEEE Access, 2021 Dynamic positron emission tomography (PET) image reconstruction is challenging due to the low-count statistics of individual frames. This study proposes a novel reconstruction framework aiming to enhance the quantitative accuracy of individual dynamic ...
Shuangliang Cao +5 more
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Maximum a posteriori Threshold Genomic Prediction Model for Ordinal Traits
G3: Genes, Genomes, Genetics, 2020 Due to the ever-increasing data collected in genomic breeding programs, there is a need for genomic prediction models that can deal better with big data.
Abelardo Montesinos-López +3 more
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Improving Serial Detection Using MAP Algorithm for Bit-Patterned Media Recording
Applied Sciences, 2022 Bit-patterned media recording (BPMR) is a promising technology for increasing the areal density (AD) of magnetic data storage systems. In BPMR, the non-magnetic zone is reduced to increase AD, which causes serious problems such as two-dimensional (2D ...
Thien An Nguyen, Jaejin Lee
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Efficient exact maximum a posteriori computation for bayesian SNP genotyping in polyploids. [PDF]
PLoS ONE, 2012 The problem of genotyping polyploids is extremely important for the creation of genetic maps and assembly of complex plant genomes. Despite its significance, polyploid genotyping still remains largely unsolved and suffers from a lack of statistical ...
Oliver Serang +2 more
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