About: A functional perspective on machine learning via programmable induction and abduction

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type	http://eprints.org/ontology/ConferenceItemEPrint http://eprints.org/ontology/EPrint Article Academic Article
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Title	A functional perspective on machine learning via programmable induction and abduction
described by	https://demo.openlinksw.com/about/id/entity/https/www.cs.kent.ac.uk/people/staff/akj22/materials/CO644/export_kar_RDFN3.n3
Date	2018-04-24
Creator	Dan R. Ghica Victor Darvariu Koko Muroya Steven Cheung Reuben N. S. Rowe
status	peer reviewed published
Publisher	Springer
abstract	We present a programming language for machine learning based on the concepts of ‘induction’ and ‘abduction’ as encountered in Peirce’s logic of science. We consider the desirable features such a language must have, and we identify the ‘abductive decoupling’ of parameters as a key general enabler of these features. Both an idealised abductive calculus and its implementation as a PPX extension of OCaml are presented, along with several simple examples.
Is Part Of	Financial Cryptography and Data Security https://kar.kent.ac.uk/id/repository
list of authors	https://kar.kent.ac.uk/id/eprint/66447#authors
presented at	Fourteenth International Symposium on Functional and Logic Programming (FLOPS 2018)
is topic of	https://www.cs.kent.ac.uk/people/staff/akj22/materials/CO644/export_kar_RDFN3.n3
is primary topic of	HTML Summary of #66447 A functional perspective on machine learning via programmable induction and abduction

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