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Learning graphical models from a distributed stream

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Zhang, Y., Tirthapura, S. and Cormode, Graham (2018) Learning graphical models from a distributed stream. In: International Conference on Data Engineering (ICDE), 2018, Paris, France, 16–19 Apr 2018

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Official URL: https://icde2018.org/

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Abstract

A current challenge for data management systems is to support the construction and maintenance of machine learning models over data that is large, multi-dimensional, and evolving. While systems that could support these tasks are emerging, the need to scale to distributed, streaming data requires new models and algorithms. In this setting, as well as computational scalability and model accuracy, we also need to minimize the amount of communication between distributed processors, which is the chief component of latency. We study Bayesian Networks, the workhorse of graphical models, and present a communication-efficient method for continuously learning and maintaining a Bayesian network model over data that is arriving as a distributed stream partitioned across multiple processors. We show a strategy for maintaining model parameters that leads to an exponential reduction in communication when compared with baseline approaches to maintain the exact MLE (maximum likelihood estimation). Meanwhile, our strategy provides similar prediction errors for the target distribution and for classification tasks.

Item Type: Conference Item (Paper)
Subjects: Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Divisions: Faculty of Science > Computer Science
Library of Congress Subject Headings (LCSH): Database management, Machine learning, Big data, Bayesian statistical decision theory
Publisher: IEEE
Official Date: 2018
Dates:
DateEvent
2018Available
26 February 2018Accepted
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
ERC-2014-CoG 647557H2020 European Research Councilhttp://dx.doi.org/10.13039/100010663
Wolfson Research Merit AwardRoyal Societyhttp://dx.doi.org/10.13039/501100000288
1527541National Science Foundationhttp://dx.doi.org/10.13039/100000001
1725702National Science Foundationhttp://dx.doi.org/10.13039/100000001
Conference Paper Type: Paper
Title of Event: International Conference on Data Engineering (ICDE), 2018
Type of Event: Conference
Location of Event: Paris, France
Date(s) of Event: 16–19 Apr 2018

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