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Towards Scalable Spatial Probabilistic Graphical Modeling

Published: 05 November 2019 Publication History

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References

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S. Balbi et al. A Spatial Bayesian Network Model to Assess the Benefits of Early Warning for Urban Flood Risk to People. Natural Hazards and Earth System Sciences, 2016.
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J. Besag. Spatial Interaction and the Statistical Analysis of Lattice Systems. Royal Statistical Society Journal, 1974.
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bnspatial: Spatial Implementation of Bayesian Networks. cran.r-project.org/web/packages/bnspatial, 2019.
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EBird Data. ebird.org/science/download-ebird-data-products.
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P. J. Green and S. Richardson. Hidden Markov Models and Disease Mapping. JASA, pages 1055--1070, 2002.
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J. Hughes. ngspatial: A Package for Fitting the Centered Autologistic and Sparse Spatial Generalized Linear Mixed Models for Areal Data. The R Journal, 2014.
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M. Kaiser et al. Goodness of Fit Tests for a Class of Markov Random Field Models. The Annals of Statistics, pages 104--130, 2012.
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F. Niu et al. Tuffy: Scaling Up Statistical Inference in Markov Logic Networks Using an RDBMS. PVLDB, 4(6):373--384, 2011.
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M. Richardson and P. M. Domingos. Markov Logic Networks. Machine Learning, pages 107--136, 2006.
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I. Sabek, M. Musleh, and M. Mokbel. TurboReg: A Framework for Scaling Up Spatial Logistic Regression Models. In SIGSPATIAL, pages 129--138, 2018.
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I. Sabek, M. Musleh, and M. F. Mokbel. A Demonstration of Sya: A Spatial Probabilistic Knowledge Base Construction System. In SIGMOD, 2018.
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S. Shekhar et al. Identifying Patterns in Spatial Information: A Survey of Methods. WIRES: Data Mining and Knowledge Discovery, pages 193--214, 2011.
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J. Shin et al. Incremental Knowledge Base Construction Using DeepDive. PVLDB, 8(11):1310--1321, 2015.
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shmm: An R Implementation of Spatial Hidden Markov Models. github.com/mawp/shmm, 2019.
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M. Wick et al. Scalable Probabilistic Databases with Factor Graphs and MCMC. PVLDB, 3(1-2):794--804, 2010.

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cover image ACM Conferences
SIGSPATIAL '19: Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
November 2019
648 pages
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Publication History

Published: 05 November 2019

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Author Tags

  1. Markov Logic Networks
  2. Scalability
  3. Spatial Analysis
  4. Spatial Probabilistic Graphical Models

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SIGSPATIAL '19 Paper Acceptance Rate 34 of 161 submissions, 21%;
Overall Acceptance Rate 257 of 1,238 submissions, 21%

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