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Federico Sabbatini
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Journal Articles
- 2024
- [j4]Federico Sabbatini, Roberta Calegari:
On the evaluation of the symbolic knowledge extracted from black boxes. AI Ethics 4(1): 65-74 (2024) - [j3]Giovanni Ciatto
, Federico Sabbatini
, Andrea Agiollo
, Matteo Magnini
, Andrea Omicini
:
Symbolic Knowledge Extraction and Injection with Sub-symbolic Predictors: A Systematic Literature Review. ACM Comput. Surv. 56(6): 161:1-161:35 (2024) - 2023
- [j2]Federico Sabbatini, Giovanni Ciatto, Roberta Calegari, Andrea Omicini:
Towards a unified model for symbolic knowledge extraction with hypercube-based methods. Intelligenza Artificiale 17(1): 63-75 (2023) - 2022
- [j1]Federico Sabbatini, Giovanni Ciatto, Roberta Calegari, Andrea Omicini:
Symbolic knowledge extraction from opaque ML predictors in PSyKE: Platform design & experiments. Intelligenza Artificiale 16(1): 27-48 (2022)
Conference and Workshop Papers
- 2023
- [c15]Federico Sabbatini, Roberta Calegari:
Unveiling Opaque Predictors via Explainable Clustering: The CReEPy Algorithm. BEWARE@AI*IA 2023: 1-14 - [c14]Federico Sabbatini
, Roberta Calegari
:
Achieving Complete Coverage with Hypercube-Based Symbolic Knowledge-Extraction Techniques. ECAI Workshops (1) 2023: 179-197 - [c13]Federico Sabbatini
, Roberta Calegari
:
Symbolic Knowledge-Extraction Evaluation Metrics: The FiRe Score. ECAI 2023: 2033-2040 - [c12]Federico Sabbatini
, Roberta Calegari
:
Bottom-Up and Top-Down Workflows for Hypercube- And Clustering-Based Knowledge Extractors. EXTRAAMAS 2023: 116-129 - [c11]Federico Sabbatini, Roberta Calegari:
ExACT Explainable Clustering: Unravelling the Intricacies of Cluster Formation. KoDis+CAKR@KR 2023 - [c10]Federico Sabbatini, Roberta Calegari:
Explainable Clustering with CREAM. KR 2023: 593-603 - [c9]Federico Sabbatini, Roberta Calegari:
Unlocking Insights and Trust: The Value of Explainable Clustering Algorithms for Cognitive Agents. WOA 2023: 232-245 - 2022
- [c8]Roberta Calegari
, Federico Sabbatini
:
The PSyKE Technology for Trustworthy Artificial Intelligence. AI*IA 2022: 3-16 - [c7]Federico Sabbatini
, Giovanni Ciatto
, Andrea Omicini
:
Semantic Web-Based Interoperability for Intelligent Agents with PSyKE. EXTRAAMAS@AAMAS 2022: 124-142 - [c6]Federico Sabbatini, Roberta Calegari:
Symbolic Knowledge Extraction from Opaque Machine Learning Predictors: GridREx & PEDRO. KR 2022 - [c5]Federico Sabbatini, Giovanni Ciatto, Roberta Calegari, Andrea Omicini:
Hypercube-based methods for symbolic knowledge extraction: towards a unified model. WOA 2022: 48-60 - 2021
- [c4]Federico Sabbatini
, Giovanni Ciatto
, Andrea Omicini
:
GridEx: An Algorithm for Knowledge Extraction from Black-Box Regressors. EXTRAAMAS@AAMAS 2021: 18-38 - [c3]Federico Sabbatini, Giovanni Ciatto, Roberta Calegari, Andrea Omicini:
On the Design of PSyKE: A Platform for Symbolic Knowledge Extraction. WOA 2021: 29-48 - 2020
- [c2]Federico Sabbatini, Sergio Tasso, Simonetta Pallottelli, Osvaldo Gervasi
:
Improvements to the G-Lorep Federation of Learning Object Repositories. ICCSA (7) 2020: 526-537 - 2019
- [c1]Sergio Tasso, Simonetta Pallottelli, Osvaldo Gervasi
, Federico Sabbatini, Valentina Franzoni, Antonio Laganà:
Cloud and Local Servers for a Federation of Molecular Science Learning Object Repositories. ICCSA (6) 2019: 359-373
Informal and Other Publications
- 2023
- [i4]Federico Sabbatini, Catia Grimani:
Solar Wind Speed Estimate with Machine Learning Ensemble Models for LISA. CoRR abs/2302.06740 (2023) - 2022
- [i3]Federico Sabbatini, Catia Grimani:
Symbolic Knowledge Extraction from Opaque Predictors Applied to Cosmic-Ray Data Gathered with LISA Pathfinder. CoRR abs/2209.04697 (2022) - [i2]Federico Sabbatini, Roberta Calegari:
Clustering-Based Approaches for Symbolic Knowledge Extraction. CoRR abs/2211.00234 (2022) - [i1]Federico Sabbatini, Roberta Calegari:
Evaluation Metrics for Symbolic Knowledge Extracted from Machine Learning Black Boxes: A Discussion Paper. CoRR abs/2211.00238 (2022)
Coauthor Index
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