Bellatreccia, C.; Zama, D.; Dondi, A.; Pierantoni, L.; Laura, A.; Neri, I.; Lanari, M.; Borghesi, A.; Calegari, R., Addressing Bias and Data Scarcity in AI-Based Skin Disease Diagnosis with Non-Dermoscopic Images, in: CEUR Workshop Proceedings, CEUR-WS, «CEUR WORKSHOP PROCEEDINGS», 2025, 3961, pp. 1 - 14 (atti di: 2nd Workshop on AI Bias: Measurements, Mitigation, Explanation Strategies, AIMMES 2025, Spain, 2025) [Contributo in Atti di convegno]
Ciatto, G.; Matteini, M.; Sartori, L.; Rebrean, M.; Muller, C.; Borghesi, A.; Calegari, R., AI-fairness: the FAIRBRIDGE approach to practically bridge the gap between socio-legal and technical perspectives, in: Proceedings of the Annual Hawaii International Conference on System Sciences, IEEE Computer Society, «PROCEEDINGS OF THE ANNUAL HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES», 2025, pp. 6504 - 6513 (atti di: 58th Hawaii International Conference on System Sciences, HICSS 2025, usa, 2025) [Contributo in Atti di convegno]
Artioli, Marcello; Borghesi, Andrea; Chinnici, Marta; Ciampolini, Anna; Colonna, Michele; De Chiara, Davide; Loreti, Daniela, C6EnPLS: A High-Performance Computing Job Dataset for the Analysis of Linear Solvers’ Power Consumption, «FUTURE INTERNET», 2025, 17, Article number: 203, pp. 1 - 18 [articolo]Open Access
Andrea Borghesi, Roberta Calegari, Generation of Clinical Skin Images with Pathology with Scarce Data, in: AI for Health Equity and Fairness, «STUDIES IN COMPUTATIONAL INTELLIGENCE», 2024, 1164, pp. 47 - 64 (atti di: THE 8th INTERNATIONAL WORKSHOP ON HEALTH INTELLIGENCE, Vancouver, Canada, 27-27 Febbraio 2024) [Contributo in Atti di convegno]
Molan, M.; Seyedkazemi Ardebili, Mohsen; Khan, J. A.; Beneventi, F.; Cesarini, D.; Borghesi, A.; Bartolini, A., GRAAFE: GRaph anomaly anticipation framework for exascale HPC systems, «FUTURE GENERATION COMPUTER SYSTEMS», 2024, 160, pp. 644 - 653 [articolo]Open Access
Farooq, Emmen; Milano, Michela; Borghesi, Andrea, Harnessing federated learning for anomaly detection in supercomputer nodes, «FUTURE GENERATION COMPUTER SYSTEMS», 2024, 161, pp. 673 - 685 [articolo]
Farooq, Emmen; Borghesi, Andrea, LSTM-Based Unsupervised Anomaly Detection in High-Performance Computing: A Federated Learning Approach, in: 2024 IEEE International Conference on Big Data (BigData), «... IEEE INTERNATIONAL CONFERENCE ON BIG DATA», 2024, pp. 7735 - 7744 (atti di: 2024 IEEE International Conference on Big Data (BigData), Washington, DC, USA, 15-18 December 2024) [Contributo in Atti di convegno]Open Access
De Filippo A.; Di Giacomo E.; Borghesi A., Machine learning approaches to predict the execution time of the meteorological simulation software COSMO, «JOURNAL OF INTELLIGENT INFORMATION SYSTEMS», 2024, x, pp. 1 - 25 [articolo]
Antici, F.; Borghesi, A.; Kiziltan, Z., Online Job Failure Prediction in an HPC System, in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND, Springer Science and Business Media Deutschland GmbH, «LECTURE NOTES IN COMPUTER SCIENCE», 2024, 14352, pp. 167 - 179 (atti di: International workshops held at the 29th International Conference on Parallel and Distributed Computing, Euro-Par 2023, cyprus, 2023) [Contributo in Atti di convegno]
Zama, D.; Borghesi, A.; Ranieri, A.; Manieri, E.; Pierantoni, L.; Andreozzi, L.; Dondi, A.; Neri, I.; Lanari, M.; Calegari, R., Perspectives and Challenges of Telemedicine and Artificial Intelligence in Pediatric Dermatology, «CHILDREN», 2024, 11, Article number: 1401, pp. 1 - 21 [articolo]Open Access
Farooq, Emmen; Borghesi, Andrea, A Federated Learning Approach for Anomaly Detection in High Performance Computing, in: 2023 IEEE 35th International Conference on Tools with Artificial Intelligence (ICTAI), New York, IEEE, 2023, pp. 496 - 500 (atti di: International Conference on Tools with Artificial Intelligence (ICTAI), Atlanta, GA, USA, 06-08 November 2023) [Contributo in Atti di convegno]Open Access
Borghesi, Andrea; Burrello, Alessio; Bartolini, Andrea, ExaMon-X: a Predictive Maintenance Framework for Automatic Monitoring in Industrial IoT Systems, «IEEE INTERNET OF THINGS JOURNAL», 2023, 10, pp. 2995 - 3005 [articolo]Open Access
Molan M.; Ahmed Khan J.; Borghesi A.; Bartolini A., Graph Neural Networks for Anomaly Anticipation in HPC Systems, in: Companion of the 2023 ACM/SPEC International Conference on Performance Engineering, 2023, pp. 239 - 244 (atti di: International Conference on Performance Engineering, Coimbra, Portugal, April 2023) [Contributo in Atti di convegno]
Molan M.; Borghesi A.; Benini L.; Bartolini A., Machine Learning Methodologies to Support HPC Systems Operations: Anomaly Detection, in: Euro-Par 2022: Parallel Processing Workshops. Euro-Par 2022, Cham, Springer, «LECTURE NOTES IN COMPUTER SCIENCE», 2023, 13835 LNCS, pp. 294 - 298 (atti di: Euro-Par 2022: Parallel Processing Workshops. Euro-Par 2022, Glasgow (Scotland), 22-26 Agosto 2022) [Contributo in Atti di convegno]Open Access
Molan, G; Dolinar, G; Bojkovski, J; Prodan, R; Borghesi, A; Molan, M, Model for Quantitative Estimation of Functionality Influence on the Final Value of a Software Product, «IEEE ACCESS», 2023, 11, Article number: 10286843, pp. 115599 - 115616 [articolo]Open Access
