| # | Authors | Title | Details | Date | Pdf/Links/Bibtex | Keywords |
|---|---|---|---|---|---|---|
| 3 | Kopanja M., Savic M., Longo L | Enhancing Cost-Sensitive Tree-Based XAI Surrogate Method: Exploring Alternative Cost Matrix Formulation | Joint Proceedings of the xAI 2025 Late-breaking Work, Demos and Doctoral Consortium co-located with the 3rd World Conference on eXplainable Artificial Intelligence (xAI 2025) | 2025 |  
@inproceedings{, title={Enhancing Cost-Sensitive Tree-Based XAI Surrogate Method: Exploring Alternative Cost Matrix Formulation}, author={Kopanja, Marija and Savi?, Miloš and Longo, Luca}, year={2025}, booktitle = {Joint Proceedings of the xAI 2025 Late-breaking Work, Demos and Doctoral Consortium co-located with the 3rd World Conference on eXplainable Artificial Intelligence (xAI 2025), Istanbul, Turkey, 9-11 July, 2025}, publisher = {CEUR-WS.org}, volume = {4017}, series = {{CEUR} Workshop Proceedings}, editor = {Przemys?aw Biecek, Slawomir Nowaczyk, Gitta Kutyniok, Luca Longo}, pages={129-136}, url={https://ceur-ws.org/Vol-4017/paper_17.pdf} } [Close]
| Explainable artificial intelligence • Cost-sensitive decision tree • Surrogate modeling • Rule extraction • Tree-based
methods • Model-agnostic explanations • Rule-based systems • Interpretability • Machine Learning. |
| 2 | Vilone G., Longo L. | A Quantitative Evaluation of Global, Rule-Based Explanations of Post-Hoc, Model Agnostic Methods | Frontiers in Artificial Intelligence | 2021 |  
@ARTICLE{ViloneLongo2021, AUTHOR={Vilone, Giulia and Longo, Luca}, TITLE={A Quantitative Evaluation of Global, Rule-Based Explanations of Post-Hoc, Model Agnostic Methods}, JOURNAL={Frontiers in Artificial Intelligence}, VOLUME={4}, PAGES={160}, YEAR={2021}, URL={https://www.frontiersin.org/article/10.3389/frai.2021.717899}, DOI={10.3389/frai.2021.717899}, ISSN={2624-8212} } [Close]
| explainable artificial intelligence • rule extraction • method comparison and evaluation • metrics of
explainability • method automatic ranking • artificial intelligence • explainability |
| 1 | Vilone G., Rizzo L., Longo L. | A comparative analysis of rule-based, model-agnostic methods for explainable artificial intelligence | Proceedings for the 28th AIAI Irish Conference on Artificial Intelligence and Cognitive Science, Dublin, Ireland, December 7-8, 2020 | 2020 |
@inproceedings{DBLP:conf/aics/ViloneRL20, author = {Giulia Vilone and Lucas Rizzo and Luca Longo}, editor = {Luca Longo and Lucas Rizzo and Elizabeth Hunter and Arjun Pakrashi}, title = {A comparative analysis of rule-based, model-agnostic methods for explainable artificial intelligence}, booktitle = {Proceedings of The 28th Irish Conference on Artificial Intelligence and Cognitive Science, Dublin, Republic of Ireland, December 7-8, 2020}, series = {{CEUR} Workshop Proceedings}, volume = {2771}, pages = {85--96}, publisher = {CEUR-WS.org}, year = {2020}, url = {http://ceur-ws.org/Vol-2771/AICS2020\_paper\_33.pdf} } [Close]
| Explainable artificial intelligence • Rule extraction • Method • comparison • evaluation |
| # | Authors | Title | Details | Date | Pdf/Links/Bibtex | Keywords |