Per Year
@article{hypercubeske-ia17, author = {Sabbatini, Federico and Ciatto, Giovanni and Calegari, Roberta and Omicini, Andrea}, dblp = {journals/ia/SabbatiniCCO23}, doi = {10.3233/IA-230001}, editor = {Ferrando, Angelo and Mascardi, Viviana}, iris = {11585/941033}, journal = {Intelligenza Artificiale}, keywords = {explainable AI, knowledge extraction, interpretable prediction, PSyKE}, month = jun, note = {Special issue: Selected papers from the 23rd Workshop ``From Objects to Agents'' (WOA 2022)}, number = 1, numpages = 13, pages = {63--75}, publisher = {IOS Press}, scholar = {14669296704428238758}, scopus = {2-s2.0-85168332389}, semanticscholar = {259324728}, title = {Towards a Unified Model for Symbolic Knowledge Extraction with Hypercube-Based Methods}, url = {https://content.iospress.com/articles/intelligenza-artificiale/ia230001}, urlopenaccess = {https://cris.unibo.it/retrieve/3a2a510e-9dc5-4b07-b3f7-398cf2f21419/ia-2023-psyke.pdf}, volume = 17, year = 2023 }
@article{psyke-ia16, author = {Sabbatini, Federico and Ciatto, Giovanni and Calegari, Roberta and Omicini, Andrea}, dblp = {journals/ia/SabbatiniCCO22}, doi = {10.3233/IA-210120}, editor = {Calegari, Roberta and Ciatto, Giovanni and Omicini, Andrea and Vizzari, Giuseppe}, eissn = {2211-0097}, iris = {11585/890822}, issn = {1724-8035}, journal = {Intelligenza Artificiale}, keywords = {Explainable AI, knowledge extraction, interpretable prediction, PSyKE}, month = jul, number = 1, numpages = 22, pages = {27--48}, publisher = {IOS Press}, scholar = {7559675640918015038}, scopus = {2-s2.0-85134193338}, semanticscholar = {250400188}, title = {Symbolic knowledge extraction from opaque {ML} predictors in {PSyKE}: Platform design \& experiments}, url = {https://content.iospress.com/articles/intelligenza-artificiale/ia220141}, volume = 16, wos = {WOS:000825367300003}, year = 2022 }
@inproceedings{skemetrics-xaifin2022, address = {New York, NY, USA}, author = {Sabbatini, Federico and Calegari, Roberta}, booktitle = {Workshop on Explainable AI in Finance @ICAIF 2022}, doi = {10.48550/arXiv.2211.00238}, keywords = {Explainable artificial intelligence; Symbolic knowledge extraction; Readability metrics; AutoML}, month = {November 2}, scholar = {5021962022669458541}, semanticscholar = {253244189}, title = {Evaluation Metrics for Symbolic Knowledge Extracted from Machine Learning Black Boxes: A Discussion Paper}, url = {https://arxiv.org/abs/2211.00238}, urlopenaccess = {https://arxiv.org/abs/2211.00238}, year = 2022 }
@incollection{hypercube-woa2022, author = {Sabbatini, Federico and Ciatto, Giovanni and Calegari, Roberta and Omicini, Andrea}, booktitle = {WOA 2022 -- 23rd Workshop ``From Objects to Agents''}, dblp = {conf/woa/SabbatiniCCO22}, editor = {Ferrando, Angelo and Mascardi, Viviana}, iris = {11585/899358}, issn = {1613-0073}, keywords = {Explainable AI; Knowledge extraction; Interpretable prediction; PSyKE}, month = nov, numpages = 13, pages = {48--60}, publisher = {Sun SITE Central Europe, RWTH Aachen University}, scholar = {8614662013642803891}, scopus = {2-s2.0-85142519111}, semanticscholar = {253270041}, series = {CEUR Workshop Proceedings}, subseries = {AIxIA Series}, title = {Hypercube-Based Methods for Symbolic Knowledge Extraction: Towards a Unified Model}, url = {http://ceur-ws.org/Vol-3261/paper4.pdf}, urlopenaccess = {http://ceur-ws.org/Vol-3261/paper4.pdf}, urlpdf = {http://ceur-ws.org/Vol-3261/paper4.pdf}, volume = 3261, year = 2022 }