Block-Coordinate Descent Algorithm for Interventional Data in Directed Graphical Models

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F25%3A00636889" target="_blank" >RIV/67985807:_____/25:00636889 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Block-Coordinate Descent Algorithm for Interventional Data in Directed Graphical Models
Original language description
Computing maximum likelihood estimates in linear structural equation models is generally a difficult problem. The critical equations are usually non-linear and have numerous solutions, even for purely observational data. The block-coordinate descent (BCD) algorithm proposed by Drton et al. (2019)[1] is an efficient way to solve the optimization problem by decomposing it into a series of sub-problems with closed-form solutions, and which works with observational data. In this work, we describe the general problem of a BCD-type scheme for computing maximum likelihood estimates in linear structural equation models without hidden variables, integrating multiple observational and interventional environments. With interventional data, the degrees of both the original likelihood equations and the block-coordinate update equations could increase greatly. We study special setups in which the block optimization subproblems have a degree of at most 2 and provide closed-form solutions in these cases. Additionally, we discuss the potential applications of the model and algorithm to health and well-being data.
Czech name
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Czech description
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Project
<a href="/en/project/EH22_008%2F0004583" target="_blank" >EH22_008/0004583: Research of Excellence on Digital Technologies and Wellbeing</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 13th Workshop on Uncertainty Processing (WUPES’25)
ISBN
978-80-7378-525-3
ISSN
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e-ISSN
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Number of pages
12
Pages from-to
200-211
Publisher name
MatfyzPress
Place of publication
Prague
Event location
Třešť
Event date
Jun 4, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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