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Bayesian Multinomial Logistic Normal Models through Marginally Latent Matrix-T Processes

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Bibliographic Details
Published in:Journal of Machine Learning Research
Format: Online Article RSS Article
Published: 2026
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container_title Journal of Machine Learning Research
description
discipline_display Education
discipline_facet Education
format Online Article
RSS Article
genre Journal Article
id rss_article:39616
institution FRELIP
journal_source_facet Journal of Machine Learning Research
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Bayesian Multinomial Logistic Normal Models through Marginally Latent Matrix-T Processes
— — — — — — e-Learning
Educational Technology
Education
sub_discipline_display Educational Technology
sub_discipline_facet Educational Technology
subject_display — — — — — — e-Learning
Educational Technology
Education
— — — — — — e-Learning
Educational Technology
Education
subject_facet — — — — — — e-Learning
Educational Technology
Education
title Bayesian Multinomial Logistic Normal Models through Marginally Latent Matrix-T Processes
title_auth Bayesian Multinomial Logistic Normal Models through Marginally Latent Matrix-T Processes
title_full Bayesian Multinomial Logistic Normal Models through Marginally Latent Matrix-T Processes
title_fullStr Bayesian Multinomial Logistic Normal Models through Marginally Latent Matrix-T Processes
title_full_unstemmed Bayesian Multinomial Logistic Normal Models through Marginally Latent Matrix-T Processes
title_short Bayesian Multinomial Logistic Normal Models through Marginally Latent Matrix-T Processes
title_sort bayesian multinomial logistic normal models through marginally latent matrix-t processes
topic — — — — — — e-Learning
Educational Technology
Education
url http://jmlr.org/papers/v23/19-882.html