Huaduo Wang, Gopal Gupta. FOLD-R++: A Scalable Toolset for Automated Inductive Learning of Default Theories from Mixed Data. In Michael Hanus, Atsushi Igarashi, editors, Functional and Logic Programming - 16th International Symposium, FLOPS 2022, Kyoto, Japan, May 10-12, 2022, Proceedings. Volume 13215 of Lecture Notes in Computer Science, pages 224-242, Springer, 2022. [doi]
@inproceedings{WangG22-1,
title = {FOLD-R++: A Scalable Toolset for Automated Inductive Learning of Default Theories from Mixed Data},
author = {Huaduo Wang and Gopal Gupta},
year = {2022},
doi = {10.1007/978-3-030-99461-7_13},
url = {https://doi.org/10.1007/978-3-030-99461-7_13},
researchr = {https://researchr.org/publication/WangG22-1},
cites = {0},
citedby = {0},
pages = {224-242},
booktitle = {Functional and Logic Programming - 16th International Symposium, FLOPS 2022, Kyoto, Japan, May 10-12, 2022, Proceedings},
editor = {Michael Hanus and Atsushi Igarashi},
volume = {13215},
series = {Lecture Notes in Computer Science},
publisher = {Springer},
isbn = {978-3-030-99461-7},
}