A Java Toolbox for Analysis of MassIve Data STreams using Probabilistic Graphical Models

Andres Masegosa, Ana Maria Martinez, Darío Ramos-López, Helge Langseth, Thomas Dyhre Nielsen, Antonio Salmerón, Rafael Cabanas, Anders Læsø Madsen

Research output: Contribution to conference without publisher/journalPosterResearchpeer-review

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Abstract

Description:
• Analysis of big data streams: A complete collection of algorithms for inference and learning of both static and dynamic Bayesian networks from streaming data. Existing software systems for PGMs only focus on stationary datasets.
• Distributed parallel algorithms: AMIDST provides parallel multi-core and distributed implementations of Bayesian parameter learning, using streaming variational Bayes and variational message passing.
Original languageEnglish
Publication date2016
Publication statusPublished - 2016
EventEuropean Data Forum 2016: EDF - Eindhoven, Netherlands
Duration: 29 Jun 201630 Jun 2016
http://2016.data-forum.eu

Conference

ConferenceEuropean Data Forum 2016
Country/TerritoryNetherlands
CityEindhoven
Period29/06/201630/06/2016
Internet address

Keywords

  • Java
  • Data streams
  • Parallel algorithms

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