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Time-Lag Aware Latent Variable Model for Prediction of Important Scenes Using Baseball Videos and Tweets [PDF]
Sensors, 2022 In this study, a novel prediction method for predicting important scenes in baseball videos using a time-lag aware latent variable model (Tl-LVM) is proposed.
Kaito Hirasawa +3 more
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Measuring domestic violence against Egyptian women and its consequent cost using a latent variable model [PDF]
BMC Women's HealthBackground Domestic Violence is a threatening worldwide problem. Its consequences against women can be dramatic, as it negatively affects women’s quality of life reflected in their general wellbeing including physical, mental, emotional and sexual health,
Mai Sherif Hafez +2 more
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Multi-Scale Multi-Kernel Gaussian Process Latent Variable Model [PDF]
Jisuanji gongcheng, 2021 As an unsupervised Bayesian non-parameter dimension reduction model,the Gaussian Process Latent Variable Model(GPLVM) fails to efficiently utilize semantic label information of data.Moreover,it just assumes that the features of all observed variables are
ZHOU Peichun, WU Lan'an
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Discussion: Latent variable graphical model selection via convex optimization [PDF]
, 2012 Discussion of "Latent variable graphical model selection via convex optimization" by Venkat Chandrasekaran, Pablo A. Parrilo and Alan S. Willsky [arXiv:1008.1290].Comment: Published in at http://dx.doi.org/10.1214/12-AOS984 the Annals of Statistics ...
Giraud, Christophe, Tsybakov, Alexandre
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Stated consideration and attribute thresholds in mode choice models: a hierarchical ICLV approach
European Journal of Transport and Infrastructure Research, 2021 Consideration of alternatives, as many other aspects related to the decision-making process, is not observable and challenging to measure. Even when supplementary information is collected during stated choice experiments, its use as an additional ...
Mauro Capurso +2 more
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A Gaussian Process Latent Variable Model for Subspace Clustering
Complexity, 2021 Effective feature representation is the key to success of machine learning applications. Recently, many feature learning models have been proposed. Among these models, the Gaussian process latent variable model (GPLVM) for nonlinear feature learning has ...
Shangfang Li
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Entropy, 2022 Latent variable models (LVMs) for neural population spikes have revealed informative low-dimensional dynamics about the neural data and have become powerful tools for analyzing and interpreting neural activity.
Yicong Huang, Zhuliang Yu
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Chinese Character Image Completion Using a Generative Latent Variable Model
Applied Sciences, 2021 Chinese characters in ancient books have many corrupted characters, and there are cases in which objects are mixed in the process of extracting the characters into images. To use this incomplete image as accurate data, we use image completion technology,
In-su Jo, Dong-bin Choi, Young B. Park
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Incremental Learning of Latent Forests
IEEE Access, 2020 In the analysis of real-world data, it is useful to learn a latent variable model that represents the data generation process. In this setting, latent tree models are useful because they are able to capture complex relationships while being easily ...
Fernando Rodriguez-Sanchez +2 more
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The Q-Matrix Anchored Mixture Rasch Model
Frontiers in Psychology, 2021 Mixture item response theory (IRT) models include a mixture of latent subpopulations such that there are qualitative differences between subgroups but within each subpopulation the measure model based on a continuous latent variable holds.
Ming-Chi Tseng, Wen-Chung Wang
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