Scaling up Bayesian variational inference using distributed computing clusters

Andrés R. Masegosa, Ana M. Martinez, Helge Langseth, Thomas Dyhre Nielsen, Antonio Salmerón, Darío Ramos-López, Anders Læsø Madsen

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

6 Citationer (Scopus)
OriginalsprogEngelsk
TidsskriftInternational Journal of Approximate Reasoning
Vol/bind88
Sider (fra-til)435-451
Antal sider17
ISSN0888-613X
DOI
StatusUdgivet - 1 sep. 2017

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Distributed computer systems
Distributed Computing
Variational Methods
Variational Bayes
Scaling
Bayesian Learning
MapReduce
Ascent
Evaluate
Exponential Family
Latent Variables
Factor Analysis
Linear Regression Model
Streaming
Open Source
Convergence Properties
Scalability
Machine Learning
Cover
Factor analysis

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    Masegosa, Andrés R. ; Martinez, Ana M. ; Langseth, Helge ; Nielsen, Thomas Dyhre ; Salmerón, Antonio ; Ramos-López, Darío ; Madsen, Anders Læsø. / Scaling up Bayesian variational inference using distributed computing clusters. I: International Journal of Approximate Reasoning. 2017 ; Bind 88. s. 435-451.
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    author = "Masegosa, {Andr{\'e}s R.} and Martinez, {Ana M.} and Helge Langseth and Nielsen, {Thomas Dyhre} and Antonio Salmer{\'o}n and Dar{\'i}o Ramos-L{\'o}pez and Madsen, {Anders L{\ae}s{\o}}",
    year = "2017",
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    Scaling up Bayesian variational inference using distributed computing clusters. / Masegosa, Andrés R.; Martinez, Ana M.; Langseth, Helge; Nielsen, Thomas Dyhre; Salmerón, Antonio; Ramos-López, Darío ; Madsen, Anders Læsø.

    I: International Journal of Approximate Reasoning, Bind 88, 01.09.2017, s. 435-451.

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

    TY - JOUR

    T1 - Scaling up Bayesian variational inference using distributed computing clusters

    AU - Masegosa, Andrés R.

    AU - Martinez, Ana M.

    AU - Langseth, Helge

    AU - Nielsen, Thomas Dyhre

    AU - Salmerón, Antonio

    AU - Ramos-López, Darío

    AU - Madsen, Anders Læsø

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    KW - Apache Flink

    KW - Conjugate exponential family

    KW - Probabilistic graphical models

    KW - Scalable Bayesian learning

    KW - Variational inference

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    DO - 10.1016/j.ijar.2017.06.010

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    EP - 451

    JO - International Journal of Approximate Reasoning

    JF - International Journal of Approximate Reasoning

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