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Irrelevance and Independence Relations in Quasi-Bayesian Networks [article]

Fabio Gagliardi Cozman
2013 arXiv   pre-print
The basic question in Quasi-Bayesian networks is, How can irrelevance/independence relations in Quasi-Bayesian networks be detected, enforced and exploited?  ...  This paper analyzes irrelevance and independence relations in graphical models associated with convex sets of probability distributions (called Quasi-Bayesian networks).  ...  The key technical problem in Quasi-Bayesian networks is how to detect, enforce and exploit irrelevance and independence rela tions.  ... 
arXiv:1301.7368v1 fatcat:xs6w5fabjvh3xiifwuhwh6u4bm

Computing posterior upper expectations

Fabio Gagliardi Cozman
2000 International Journal of Approximate Reasoning  
Algorithms that handle irrelevance and independence relations in multivariate models are analyzed through graphical representations, inspired by the popular Bayesian network model. Ó  ...  This article investigates the computation of posterior upper expectations induced by imprecise probabilities, with emphasis on the eects of irrelevance and independence judgements.  ...  Thanks to Jay Kadane and Paul Snow for commenting on some of the results presented in this article. The author was partially supported by CNPq, Brazil, through grant 300183-98/4.  ... 
doi:10.1016/s0888-613x(00)00034-7 fatcat:5oojgdkqc5ewxkg7ietj7iqapy

Separation Properties of Sets of Probability Measures [article]

Fabio Gagliardi Cozman
2013 arXiv   pre-print
The main result is that the strong Markov condition leads to strong independence and does enforce separation properties; this result implies that (1) separation properties of Bayesian networks do extend  ...  to epistemic independence and sets of probability measures, and (2) strong independence has a clear justification based on epistemic independence and the strong Markov condition.  ...  Acknowledgements I greatly benefited from joint work with Peter Walley on graphoid properties; I learned about Kuznetsov's independence from him.  ... 
arXiv:1301.3845v1 fatcat:lz3yumby3zerdggu3rekm4psdy

Independence for full conditional probabilities: Structure, factorization, non-uniqueness, and Bayesian networks

Fabio G. Cozman
2013 International Journal of Approximate Reasoning  
This paper characterizes the structure of full conditional probabilities under various concepts of independence; limitations of existing concepts are examined with respect to the theory of Bayesian networks  ...  A theory of Bayesian networks is proposed where full conditional probabilities are encoded using infinitesimals, with a brief discussion of hyperreal full conditional probabilities.  ...  Thanks to the reviewers for excellent reviews; in particular for clarifying Coletti and Scozzafava's concept of independence, and for suggesting a simple version of axioms for full conditional probabilities  ... 
doi:10.1016/j.ijar.2013.08.001 fatcat:bwjpgq65srdulbhcfllxdmol3m

Foundations of Mechanism Design [chapter]

Y. Narahari, Ramasuri Narayanam, Dinesh Garg, Hastagiri Prakash
2009 Game Theoretic Problems in Network Economics and Mechanism Design Solutions  
science, electronic commerce, and network economics.  ...  Mechanism design, an important tool in microeconomics, has recently found widespread applications in modeling and solving decentralized design problems in many branches of engineering, notably computer  ...  Our grateful thanks to three anonymous referees for their insightful comments and helpful suggestions.  ... 
doi:10.1007/978-1-84800-938-7_2 fatcat:hhq5hjkmb5gb3owewxj4p3lmta

Complex event processing over uncertain data

Segev Wasserkrug, Avigdor Gal, Opher Etzion, Yulia Turchin
2008 Proceedings of the second international conference on Distributed event-based systems - DEBS '08  
We experimented with both the Bayesian network and the sampling algorithms, showing the latter to be scalable under an increasing rate of explicit event delivery and an increasing number of uncertain rules  ...  The first provides an accurate, albeit expensive method based on the construction of a Bayesian network.  ...  In addition, Bayesian networks utilize probabilistic independencies to make such a representation more efficient.  ... 
doi:10.1145/1385989.1386022 dblp:conf/debs/WasserkrugGET08 fatcat:vhn4zuf5pfaurccq5b5c637bqi

Foundations of mechanism design: A tutorial Part 1-Key concepts and classical results

Dinesh Garg, Y. Narahari, Sujit Gujar
2008 Sadhana (Bangalore)  
science, electronic commerce, and network economics.  ...  Mechanism design, an important tool in microeconomics, has recently found widespread applications in modeling and solving decentralized design problems in many branches of engineering, notably computer  ...  Our grateful thanks to three anonymous referees for their insightful comments and helpful suggestions.  ... 
doi:10.1007/s12046-008-0008-3 fatcat:ntzvjfuxdzcchkaddf55macg5q

Probabilistic Inference in Influence Diagrams

Nevin Lianwen Zhang
1998 Computational intelligence  
This paper studies the relationship between probabilistic inference in Bayesian networks and evaluation of in uence diagrams.  ...  This work leads to a new method for evaluating inuence diagrams where arbitrary Bayesian network inference algorithms can be used for probabilistic inference.  ...  The paper has bene ted from discussions with David Poole and Prakash Shenoy. I a m also grateful to the anonymous reviewers and the editor Nick Cercone for valuable comments.  ... 
doi:10.1111/0824-7935.00073 fatcat:wsqesrrbrfeerg2aip36btopme

Credal Networks under Epistemic Irrelevance [article]

Jasper De Bock
2017 arXiv   pre-print
A credal network under epistemic irrelevance is a generalised type of Bayesian network that relaxes its two main building blocks.  ...  We provide numerous concrete examples of how this can be achieved, and use these to demonstrate that computing with credal networks under epistemic irrelevance is most definitely feasible, and in some  ...  I also thank the anonymous reviewers of this paper and of the two conference papers on which it is based [18, 19] , for their detailed reading and constructive feedback.  ... 
arXiv:1701.08661v2 fatcat:oioon4xxozhnpboz32egrvcnui

Credal networks under epistemic irrelevance

Jasper De Bock
2017 International Journal of Approximate Reasoning  
A credal network under epistemic irrelevance is a generalised type of Bayesian network that relaxes its two main building blocks.  ...  We provide numerous concrete examples of how this can be achieved, and use these to demonstrate that computing with credal networks under epistemic irrelevance is most definitely feasible, and in some  ...  I also thank the anonymous reviewers of this paper and of the two conference papers on which it is based [18, 19] , for their detailed reading and constructive feedback.  ... 
doi:10.1016/j.ijar.2017.03.012 fatcat:ui2s4q5ty5ar7pne7tdgluzpci

Causal Feature Selection [chapter]

Isabelle Guyon, Constantin Aliferis, Andr´e Elissee.
2007 Computational Methods of Feature Selection  
agents, and making predictions in nonstationary environments.  ...  Conversely, we highlight the benefits that causal discovery may draw from recent developments in feature selection theory and algorithms.  ...  Thus, in a faithful Bayesian networks, d-separation captures all conditional dependence and independence relations that are encoded in the graph.  ... 
doi:10.1201/9781584888796.ch4 fatcat:dui3jd46qjdfbfeyoi4fyx7tdy

Credal Networks under Maximum Entropy [article]

Thomas Lukasiewicz
2013 arXiv   pre-print
Moreover, we apply the new principle of sequential maximum entropy to interval Bayesian networks and more generally to credal networks.  ...  In detail, we start by showing that the unique joint distribution of a Bayesian tree coincides with the maximum entropy model of its conditional distributions.  ...  This work has been partially supported by a DFG grant and the Austrian Science Fund Project N Z29-INF.  ... 
arXiv:1301.3873v1 fatcat:uqyuzgb53zfvpeuuww6k5y7cby

Encoding Dependence in Bayesian Causal Networks

John J. Sulik, Nathaniel K. Newlands, Dan S. Long
2017 Frontiers in Environmental Science  
But the observations that are analyzed are not necessarily independent and are autocorrelated due to their locational positions in space and time.  ...  Given the large uncertainties facing environmental decision making, and the need for more robust prediction methods, Bayesian-hierarchical, causal-learning, and copula-based network techniques are increasingly  ...  ACKNOWLEDGMENTS JS and DL were supported by Research Grant Award No. 2012-10008-19727 from the USDA National Institute of Food and Agriculture.  ... 
doi:10.3389/fenvs.2016.00084 fatcat:salhsuloufbirjrheeorph4dka

Concept for Alarm Flood Reduction with Bayesian Networks by Identifying the Root Cause [chapter]

Paul Wunderlich, Oliver Niggemann
2018 IMPROVE - Innovative Modelling Approaches for Production Systems to Raise Validatable Efficiency  
For the causal model, a Bayesian network is used which maps the interrelations between the alarms. Based on this causal model the root cause of an alarm flood can be determined using inference.  ...  In view of the increasing amount of information in the form of alarms, messages or also acoustic signals, the operators of systems are exposed to more workload and stress than ever before.  ...  In a constrained-based method the Bayesian network is a representation of independencies.  ... 
doi:10.1007/978-3-662-57805-6_7 fatcat:w24cfoodlvavdlj3it4k3f2v2a

Antimicrobial lock solutions for the prevention of catheter-related infection in patients undergoing haemodialysis: study protocol for network meta-analysis of randomised controlled trials

Jun Zhang, Rong-Ke Li, Kee-Hsin Chen, Long Ge, Jin-Hui Tian
2016 BMJ Open  
The purpose of our study is to carry out a network meta-analysis comparing the efficacy of different ALS for prevention of CRI in patients with HD and ranking these ALS for practical consideration.  ...  Catheter-related infection (CRI) is a difficult clinical problem in renal medicine, with blood stream infections occurring in up to 40% of patients with haemodialysis (HD) catheters, conferring significant  ...  METHODS Design Bayesian network meta-analysis will be used in this study.  ... 
doi:10.1136/bmjopen-2015-010264 pmid:26733573 pmcid:PMC4716163 fatcat:nvf5ve4oz5h2fnagztuc6aq3na
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