Andrea Campagner, Federico Cabitza. Back to the Feature: A Neural-Symbolic Perspective on Explainable AI. In Andreas Holzinger, Peter Kieseberg, A Min Tjoa, Edgar R. Weippl, editors, Machine Learning and Knowledge Extraction - 4th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2020, Dublin, Ireland, August 25-28, 2020, Proceedings. Volume 12279 of Lecture Notes in Computer Science, pages 39-55, Springer, 2020. [doi]
@inproceedings{CampagnerC20-0, title = {Back to the Feature: A Neural-Symbolic Perspective on Explainable AI}, author = {Andrea Campagner and Federico Cabitza}, year = {2020}, doi = {10.1007/978-3-030-57321-8_3}, url = {https://doi.org/10.1007/978-3-030-57321-8_3}, researchr = {https://researchr.org/publication/CampagnerC20-0}, cites = {0}, citedby = {0}, pages = {39-55}, booktitle = {Machine Learning and Knowledge Extraction - 4th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2020, Dublin, Ireland, August 25-28, 2020, Proceedings}, editor = {Andreas Holzinger and Peter Kieseberg and A Min Tjoa and Edgar R. Weippl}, volume = {12279}, series = {Lecture Notes in Computer Science}, publisher = {Springer}, isbn = {978-3-030-57321-8}, }