<div class="csl-bib-body">
<div class="csl-entry">de Colnet, A., & Marquis, P. (2023). On Translations between ML Models for XAI Purposes. In <i>Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI-23)</i> (pp. 3158–3166). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2023/352</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/193325
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dc.description.abstract
In this paper, the succinctness of various ML models is studied. To be more precise, the existence of polynomial-time and polynomial-space translations between representation languages for classifiers is investigated. The languages that are considered include decision trees, random forests, several types of boosted trees, binary neural networks, Boolean multilayer perceptrons, and various logical representations of binary classifiers. We provide a complete map indicating for every pair of languages C, C' whether or not a polynomial-time / polynomial-space translation exists from C to C'. We also explain how to take advantage of the resulting map for XAI purposes.
en
dc.description.sponsorship
FWF - Österr. Wissenschaftsfonds
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dc.language.iso
en
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dc.relation.ispartofseries
IJCAI
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dc.rights.uri
http://rightsstatements.org/vocab/InC/1.0/
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dc.subject
Knowledge Representation and Reasoning
en
dc.subject
Knowledge compilation
en
dc.subject
Knowledge representation languages
en
dc.title
On Translations between ML Models for XAI Purposes
