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A formal approach to using data distributions for building causal polytree structures

M. Ouerd, B.J. Oommen, S. Matwin
<span title="">2004</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ozlq63ehnjeqxf6cuxxn27cqra" style="color: black;">Information Sciences</a> </i> &nbsp;
By using the tree structure and these independence tests, our scheme successfully orients the polytree using an application of the depth first search (DFS) strategy to multiple causal basins.  ...  The algorithm has been formally proven, and rigorously tested for synthetic and real-life data.  ...  The latter did not contain the formal theorems or proofs, nor did it contain a detailed description of the actual algorithm.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.ins.2004.01.001">doi:10.1016/j.ins.2004.01.001</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/e7qd2nfxgvdvllqq6l5k2vctvy">fatcat:e7qd2nfxgvdvllqq6l5k2vctvy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170809125310/http://people.scs.carleton.ca/~oommen/papers/PaperPolyTreePublished.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/c2/b3/c2b33f6cc5840dccabdd5417f9e560cc21fc808f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.ins.2004.01.001"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Logarithmic-Time Updates and Queries in Probabilistic Networks [article]

A. L. Delcher, A. J. Grove, S. Kasif, J. Pearl
<span title="1996-02-01">1996</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We propose a dynamic data structure that supports efficient algorithms for updating and querying singly connected Bayesian networks.  ...  We propose an algorithm which, after a preprocessing phase, allows us to answer queries in time O(log N) at the expense of O(log N) time per evidence absorption.  ...  While the answer to this question appears to be di cult, it is possible to use a more sophisticated approach to produce a data structure (which is not a causal tree) to process queries and updates in O  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/cs/9602102v1">arXiv:cs/9602102v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bjosg6jszrei7bo63frq6tg24y">fatcat:bjosg6jszrei7bo63frq6tg24y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20171008224750/https://core.ac.uk/download/pdf/2423815.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/b0/22/b022cb67811ec04831c0bd48a720dfd82d7ae529.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/cs/9602102v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Logarithmic-Time Updates and Queries in Probabilistic Networks

A. L. Delcher, A. J. Grove, S. Kasif, J. Pearl
<span title="1996-02-01">1996</span> <i title="AI Access Foundation"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4ax4efcwajcgvidb6hcg6mwx4a" style="color: black;">The Journal of Artificial Intelligence Research</a> </i> &nbsp;
We propose a dynamic data structure that supports efficient algorithms for updating and querying singly connected Bayesian networks.  ...  We propose an algorithm which, after a preprocessing phase, allows us to answer queries in time O(log N) at the expense of O(log N) time per evidence absorption.  ...  While the answer to this question appears to be di cult, it is possible to use a more sophisticated approach to produce a data structure which i s not a causal tree to process queries and updates in Olog  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1613/jair.238">doi:10.1613/jair.238</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xcsiy4vvnrbq3ckrorzjj7q3gm">fatcat:xcsiy4vvnrbq3ckrorzjj7q3gm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190429100254/https://jair.org/index.php/jair/article/download/10154/24068" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/84/97/8497708e9d67e49d7fdedcacbc50fd8ef05c0b5b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1613/jair.238"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Learning Bayesian networks: approaches and issues

Rónán Daly, Qiang Shen, Stuart Aitken
<span title="2011-05-12">2011</span> <i title="Cambridge University Press (CUP)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ppliiwuwhjhjzdhxr5qnaaqsyi" style="color: black;">Knowledge engineering review (Print)</a> </i> &nbsp;
This work takes a broad look at the literature on learning Bayesian networks-in particular their structure-from data.  ...  This article is not intended to be a tutorial-for this, there are many books on the topic, which will be presented.  ...  Stuart Aitken is funded by BBSRC grant BB/F015976/1, and by the Centre for Systems Biology at Edinburgh, a Centre for Integrative Systems Biology (CISB) funded by BBSRC and EPSRC, reference BB/ D019621  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1017/s0269888910000251">doi:10.1017/s0269888910000251</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/schmhrymdjewrggsdq7vmx23uu">fatcat:schmhrymdjewrggsdq7vmx23uu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20150420203948/http://www.research.ed.ac.uk:80/portal/files/7949745/Learning_Bayesian_networks.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/b8/77/b8775a79c21c2b3009a7f948ba8259875b16c1bd.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1017/s0269888910000251"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> cambridge.org </button> </a>

Performance Evaluation of the Parallel Polytree Approximation Distribution Algorithm on Three Network Technologies

J. Madera, E. Alba, G. Luque
<span title="2007-10-18">2007</span> <i title="IBERAMIA: Sociedad Iberoamericana de Inteligencia Artificial"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/5qve3fgne5dh3mzbzovoilyufm" style="color: black;">Inteligencia Artificial</a> </i> &nbsp;
This paper proposes two parallel versions of an Estimation of Distribution Algorithm (EDA) that represents the probability distribution by means of a single connected graphical model based on a polytree  ...  structure (PADA).  ...  One kind of algorithms for structure learning uses a score+search procedure.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.4114/ia.v11i35.901">doi:10.4114/ia.v11i35.901</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/a3cynohh2bf2boxqkybjncfg34">fatcat:a3cynohh2bf2boxqkybjncfg34</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180721035310/http://journaldocs.iberamia.org/articles/543/article%20(1).pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/90/48/90482ccc52b4dd0d3dbcf6326410f6c1803beeae.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.4114/ia.v11i35.901"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Extending ontology queries with Bayesian network reasoning

Bellandi Andrea, Turini Franco
<span title="">2009</span> <i title="IEEE"> 2009 International Conference on Intelligent Engineering Systems </i> &nbsp;
Formal ontologies are useful for data integration, particularly at the upper-most levels, because they provide for a logical structure for various categories and relations, independent of any particular  ...  This is very efficient in terms of space complexity, because we have not to use very large data structures for storing all the initial probabilities values.  ...  Appendix A Bayesian Query Language: The Operational Semantics In the following is reported the operational semantics of the Bayesian Query Language.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/ines.2009.4924756">doi:10.1109/ines.2009.4924756</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bmk2swmhw5chzbbqkr6ldhi43a">fatcat:bmk2swmhw5chzbbqkr6ldhi43a</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170922005022/http://e-theses.imtlucca.it/8/1/Bellandi_phdthesis.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/8d/e0/8de06cc479fe0aa198916ca1c9b4ac42898008c7.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/ines.2009.4924756"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Probabilistic Fault Localization in Communication Systems Using Belief Networks

M. Steinder, A.S. Sethi
<span title="">2004</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wn5qtqh7ejhpfdjtrxhija73bq" style="color: black;">IEEE/ACM Transactions on Networking</a> </i> &nbsp;
We apply Bayesian reasoning techniques to perform fault localization in complex communication systems while using dynamic, ambiguous, uncertain, or incorrect information about the system structure and  ...  We introduce adaptations of two Bayesian reasoning techniques for polytrees, iterative belief updating, and iterative most probable explanation.  ...  Building upon our previous work [49] , which maps a dependency graph into a causality graph, this paper uses a causality graph as a fault propagation model.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tnet.2004.836121">doi:10.1109/tnet.2004.836121</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rmp26hucb5htjef6ddiik23pt4">fatcat:rmp26hucb5htjef6ddiik23pt4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20060713060656/http://www.cis.udel.edu:80/~sethi/papers/04/ton04.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/72/a6/72a680315f8565725b1219ccc707050b8996dc85.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tnet.2004.836121"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

A frequency approach to topological identification and graphical modeling [article]

Giacomo Innocenti
<span title="2011-08-07">2011</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In such a scenario a frequency based method of investigation is developed to obtain useful insights on the network.  ...  The considered approach is blind, i.e., no a priori assumptions on the interconnected systems are available.  ...  Moreover, only the non-causal approach will be presented, since the causal one just differs for the numerical tools used to compute the distance matrix.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1108.1549v1">arXiv:1108.1549v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xpqejradfnfvnkchtlud5kb4jq">fatcat:xpqejradfnfvnkchtlud5kb4jq</a> </span>
<a target="_blank" rel="noopener" href="https://archive.org/download/arxiv-1108.1549/1108.1549.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> File Archive [PDF] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1108.1549v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Possibilistic conditional independence: A similarity-based measure and its application to causal network learning

Ramón Sangüesa, Joan Cabós, Ulises Cortés
<span title="">1998</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/sy2zvsxl4vdejh3zsp3utmplry" style="color: black;">International Journal of Approximate Reasoning</a> </i> &nbsp;
This definition is used to detect conditional independence relations in possibility distributions derived from data.  ...  This is the basis for a new hybrid algorithm for recovering possibilistic causal networks.  ...  For example, the CB algorithm uses dependence tests to recover a structure and uses a topological order on the resulting DAG to guide the K2 algorithm [47] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/s0888-613x(98)00012-7">doi:10.1016/s0888-613x(98)00012-7</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/jfrw44hyfjfbzm3oj4vte7oeuq">fatcat:jfrw44hyfjfbzm3oj4vte7oeuq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170925000232/http://publisher-connector.core.ac.uk/resourcesync/data/elsevier/pdf/1e7/aHR0cDovL2FwaS5lbHNldmllci5jb20vY29udGVudC9hcnRpY2xlL3BpaS9zMDg4ODYxM3g5ODAwMDEyNw%3D%3D.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ec/2d/ec2d578d9378a6d494e6b08ed05d5abf0a6e72c5.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/s0888-613x(98)00012-7"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Misper-Bayes: A Bayesian Network Model for Missing Person Investigations

Denis Reilly, Mark Taylor, Paul Fergus, Carl Chalmers, Steven Thompson
<span title="">2021</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
The approach uses a firstorder Markov transition matrix for generating a temporal, posterior predictive probability distribution map.  ...  MACHINE LEARNING AND FORMAL APPROACHES There are also several other machine learning related approaches for dealing with missing person cases.  ...  the use of home appliances to model habitual behaviours for early intervention practices and safe independent living at home.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2021.3069081">doi:10.1109/access.2021.3069081</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fv7xzk7lvjb4rdoxufpvgbl7kq">fatcat:fv7xzk7lvjb4rdoxufpvgbl7kq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210717103756/https://ieeexplore.ieee.org/ielx7/6287639/6514899/09387332.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/a5/11/a5113f53fc8d6b0dba96044e60de7418cb79d5d4.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2021.3069081"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>

Predicting human immunodeficiency virus inhibitors using multi-dimensional Bayesian network classifiers

Hanen Borchani, Concha Bielza, Carlos Toro, Pedro Larrañaga
<span title="">2013</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/7zekrk5bkbglxhzdjmkpl6hksq" style="color: black;">Artificial Intelligence in Medicine</a> </i> &nbsp;
In this paper, we introduce a new method, named MB-MBC, for learning MBCs from data by determining the Markov blanket around each class variable using the HITON algorithm.  ...  instance in the data set has to be assigned simultaneously to multiple output class variables that are not necessarily binary.  ...  Let us assume that we apply HITON algorithm to a data set coming out of the MBC structure of Fig. 1 .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.artmed.2012.12.005">doi:10.1016/j.artmed.2012.12.005</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/23375464">pmid:23375464</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vnrvoblcyzeexgiwzrrnnxfgz4">fatcat:vnrvoblcyzeexgiwzrrnnxfgz4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20130608131537/http://cig.fi.upm.es/articles/2013/Borchani2013_AIIM.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/97/cc/97ccbb6d3731bacebd75ad80bdfb37cd228a88ea.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.artmed.2012.12.005"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Expandable bayesian networks for 3D object description from multiple views and multiple mode inputs

ZuWhan Kim, R. Nevatia
<span title="">2003</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/3px634ph3vhrtmtuip6xznraqi" style="color: black;">IEEE Transactions on Pattern Analysis and Machine Intelligence</a> </i> &nbsp;
We introduce the use of hidden variables to handle correlation of evidence features across images. We show an application of an EBN to a multiview building description system.  ...  A key problem here is the evaluation of a hypothesis based on evidence that is uncertain. There have been few efforts on applying formal reasoning methods to this problem.  ...  Therefore, we use a causal EBN, where the structure of the template network is determined by causal relationships.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tpami.2003.1201825">doi:10.1109/tpami.2003.1201825</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nrbwhylevvhbpayti6y46o2jji">fatcat:nrbwhylevvhbpayti6y46o2jji</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20100724033301/http://iris.usc.edu/Outlines/papers/2003/pami03-kim-bayes.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/03/d7/03d7532267db0f2955caf8302ba0a5b67b3bfee0.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tpami.2003.1201825"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Global Conditioning for Probabilistic Inference in Belief Networks [chapter]

Ross D. Shachter, Stig.K. Andersen, Peter Szolovits
<span title="">1994</span> <i title="Elsevier"> Uncertainty Proceedings 1994 </i> &nbsp;
Nonetheless, this approach provides new opportunities for parallel processing and, in the case of sequential processing, a tradeoff of time for memory.  ...  In this paper we propose a new approach to probabilistic inference on belief networks, global conditioning, which is a simple generalization of Pearl's (1986b) method of loopcutset conditioning.  ...  We have a finite set of elements N = {1, . . . , n}, corresponding to the nodes in a directed acyclic graph.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/b978-1-55860-332-5.50070-5">doi:10.1016/b978-1-55860-332-5.50070-5</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ad64awnw25dophb5n4yg6vosgq">fatcat:ad64awnw25dophb5n4yg6vosgq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170813031339/http://web.stanford.edu/~shachter/pubs/globcond.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/36/3e/363e19feea21f26763d799ca1cd4ee4281138646.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/b978-1-55860-332-5.50070-5"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Global Conditioning for Probabilistic Inference in Belief Networks [article]

Ross D. Shachter, Stig K. Andersen, Peter Szolovits
<span title="2013-02-27">2013</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Nonetheless, this approach provides new opportunities for parallel processing and, in the case of sequential processing, a tradeoff of time for memory.  ...  In this paper we propose a new approach to probabilistic inference on belief networks, global conditioning, which is a simple generalization of Pearl's (1986b) method of loopcutset conditioning.  ...  All of the incoming cluster messages combined with the local data also allow us to compute the posterior probability distribution P, = Pr{Xs.,t} for any clusters., P; = 2::: II w k = w.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1302.6843v1">arXiv:1302.6843v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/tbemsn2agve3xkrlktlpiz6xbi">fatcat:tbemsn2agve3xkrlktlpiz6xbi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200907034234/https://arxiv.org/ftp/arxiv/papers/1302/1302.6843.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/16/fd/16fd86d67d6c7a62aa61bf253c32c5cdafeef557.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1302.6843v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Independency relationships and learning algorithms for singly connected networks

LUIS M. DE CAMPOS
<span title="">1998</span> <i title="Informa UK Limited"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/t5mpusqpirhnjlrcurxdscrpl4" style="color: black;">Journal of experimental and theoretical artificial intelligence (Print)</a> </i> &nbsp;
Graphical structures such as Bayesian networks or M arkov networks are very useful tools for representing irrelevance or independency relationships, and they may be used to e ciently perform reasoning  ...  The aim of this paper is to investigate the kind of properties that a dependency model must verify in order to be equivalent to a singly connected graph structure, as a way of driving automated discovery  ...  I am most obliged to Gregory Cooper for providing the Alarm database.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1080/095281398146743">doi:10.1080/095281398146743</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xr254qv3w5apnatffzlfog2zua">fatcat:xr254qv3w5apnatffzlfog2zua</a> </span>
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