Results 211 to 220 of about 1,485 (251)

Markov Blankets for Sustainability

2023
This paper’s aim is twofold: on the one hand, to provide an overview of the state of the art of some kind of Bayesian networks, i.e. Markov blankets (MB), focusing on their relationship with the cognitive theories of the free energy principle (FEP) and active inference.
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Choosing a Markov blanket

Behavioral and Brain Sciences, 2020
Abstract This commentary focuses upon the relationship between two themes in the target article: the ways in which a Markov blanket may be defined and the role of precision and salience in mediating the interactions between what is internal and external to a system.
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Markov blankets and the preformationist assumption

Behavioral and Brain Sciences, 2022
Abstract Bruineberg and colleagues argue that a realist interpretation of Markov blankets inadvertently relies upon unfounded assumptions. However, insofar as their diagnosis is accurate, their prescribed instrumentalism may ultimately prove insufficient as a complete remedy.
Mads Dengsø, Ian Robertson, Axel Constant   +2 more
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Markov blankets do not demarcate the boundaries of the mind

Behavioral and Brain Sciences, 2022
Abstract We agree with Bruineberg and colleagues' main claims. However, we urge for a more forceful critique by focusing on the extended mind debate. We argue that even once the Pearl and Friston versions of the Markov blanket have been untangled, that neither is sufficient for tackling and resolving the question of demarcating the boundaries of the
Richard Menary, Alexander J. Gillett
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Hybrid Markov Blanket discovery

2016 23rd International Conference on Pattern Recognition (ICPR), 2016
In a Bayesian Network (BN), a target node is independent of all other nodes given its Markov Blanket (MB). By finding the MB, many problem can be solved directly or indirectly. There exist predominately two different approaches to finding the MB: the score-based and the constraint-based algorithms.
Tian Gao, Qiang Ji
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Discovery of context-specific Markov blankets

2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583), 2005
The notion of context-specific Markov blankets (CSMB) is a refinement of Markov blankets (MB). An important property of context specific Markov-blankets is that in the worst case they need as many parameters as a model using a standard Markov blanket, but frequently considerably fewer. The result is expected to be a much improved probabilistic model of
Assaf Klein, Solomon Eyal Shimony
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Online Markov Blanket Discovery With Streaming Features

2020 IEEE International Conference on Knowledge Graph (ICKG), 2020
The Markov blanket (MB) in Bayesian networks has attracted much attention since the MB of a target attribute (T) is the minimal feature subset with maximum prediction ability for classification. Nevertheless, traditional MB discovery methods such as IAMB, HITON-MB, and MMMB are not suitable for streaming features.
Dianlong You, Ruiqi Li, Miaomiao Sun, Xinju Ou, Shunpan Liang, Fuyong Yuan   +5 more
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Markov blankets: Realism and our ontological commitments

Behavioral and Brain Sciences, 2022
Abstract The authors argue that their target is orthogonal to the realism and instrumentalist debate. I argue that it is born directly from it. While the distinction is helpful in illuminating how some ontological commitments demand a theory of implementation, it's less clear whether different views cleanly map onto the epistemic and metaphysical ...
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Classification using Markov blanket for feature selection

2009 IEEE International Conference on Granular Computing, 2009
Selecting relevant features is in demand when a large data set is of interest in a classification task. It produces a tractable number of features that are sufficient and possibly improve the classification performance. This paper studies a statistical method of Markov blanket induction algorithm for filtering features and then applies a classifier ...
Yifeng Zeng, Jian Luo, Shuyuan Lin
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Markov blanket and Markov boundary of multiple variables

J. Mach. Learn. Res., 2018
Summary: Markov blanket (Mb) and Markov boundary (MB) are two key concepts in Bayesian networks (BNs). In this paper, we study the problem of Mb and MB for multiple variables. First, we show that Mb possesses the additivity property under the local intersection assumption, that is, an Mb of multiple targets can be constructed by simply taking the union
Xu-Qing Liu, Xin-sheng Liu
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