@inproceedings{8d0dc522b56a486b995ba27e6e31afea,
title = "A functional perspective on machine learning via programmable induction and abduction",
abstract = "We present a programming language for machine learning based on the concepts of {\textquoteleft}induction{\textquoteright} and {\textquoteleft}abduction{\textquoteright} as encountered in Peirce{\textquoteright}s logic of science. We consider the desirable features such a language must have, and we identify the {\textquoteleft}abductive decoupling{\textquoteright} 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.",
author = "Steven Cheung and Victor Darvariu and Ghica, {Dan R.} and Koko Muroya and Rowe, {Reuben N. S.}",
year = "2018",
month = may,
day = "9",
doi = "10.1007/978-3-319-90686-7_6",
language = "English",
isbn = "9783319906850",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "84--89",
editor = "Gallagher, {John P.} and Martin Sulzmann",
booktitle = "Functional and Logic Programming",
note = "14th International Symposium on Functional and Logic Programming, (FLOPS 2018) ; Conference date: 09-05-2018 Through 11-05-2018",
}