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2020 – today
- 2025
[j5]Sergio Flesca, Domenico Mandaglio
, Francesco Scala:
Enhancing active learning through latent space exploration: A k-nearest neighbors approach. Array 28: 100584 (2025)- [j4]Francesco Scala, Sergio Flesca, Luigi Pontieri:
An efficient model training framework for green AI. Mach. Learn. 114(12): 275 (2025) - [c13]Liliana Martirano, Francesco Scala, Carmela Comito, Luigi Pontieri:
Who Drives Misinformation? Key Node Detection with Heterogeneous Graph Neural Networks. DS 2025: 47-62 - [c12]Francesco Scala, Massimo Guarascio, Carlo Parrotta, Luigi Pontieri:
Learning Fast to Detect Slow: A Few-Shot Neural Approach to Slow DoS Attack Detection. DS 2025: 347-362 - [c11]Luigi Pontieri, Pietro Sabatino, Francesco Scala:
AI for sustainability should be sustainable in its own: results from project FAIR-Spoke 9. Ital-IA 2025 - [c10]Alberto Falcone, Massimo Guarascio, Angelica Liguori, Francesco Sergio Pisani, Francesco Scala:
From One to Many: Few-Shot Deep Ensembles for Slow DoS Attack Detection. PKDD/ECML Workshops (2) 2025: 471-483 - [c9]Sergio Flesca, Marco Gagliardi, Danilo Maurmo, Francesco Scala, Eugenio Vocaturo:
Benchmarking Active Learning Techniques: Insights from Multi-Domain Fake News Detection. SEBD 2025: 139-154 - [i2]Bettina Fazzinga, Sergio Flesca, Filippo Furfaro, Luigi Pontieri, Francesco Scala:
Combining Abstract Argumentation and Machine Learning for Efficiently Analyzing Low-Level Process Event Streams. CoRR abs/2505.05880 (2025) - [i1]Sabri Meyer, Francesco Scala, Francesco Tacchino, Aurélien Lucchi:
Trainability of Quantum Models Beyond Known Classical Simulability. CoRR abs/2507.06344 (2025) - 2024
- [j3]Sergio Flesca, Domenico Mandaglio, Francesco Scala, Andrea Tagarelli:
A meta-active learning approach exploiting instance importance. Expert Syst. Appl. 247: 123320 (2024) - [c8]Francesco Scala, Sergio Flesca, Luigi Pontieri:
Play it Straight: An Intelligent Data Pruning Technique for Green-AI. DS (1) 2024: 69-85 - [c7]Francesco Scala, Luigi Pontieri, Sergio Flesca:
DPET: A Data and Parameter Efficient Training Framework for Green AI (SHORT PAPER). GreenAI@AI*IA 2024: 24-28 - [c6]Francesco Scala, Sergio Flesca, Luigi Pontieri:
Data Filtering for a Sustainable Model Training. SEBD 2024: 205-216 - 2023
- [c5]Sergio Flesca, Domenico Mandaglio, Francesco Scala, Andrea Tagarelli:
A Meta-Active Learning Approach Exploiting Instance Importance based on Learning Gradient Variation. SEBD 2023: 535-544 - 2022
- [j2]Sergio Flesca, Francesco Scala, Eugenio Vocaturo, Francesco Zumpano:
On forecasting non-renewable energy production with uncertainty quantification: A case study of the Italian energy market. Expert Syst. Appl. 200: 116936 (2022) - [c4]Patrizia Vizza, Giuseppe Tradigo, Raffaele Giancotti, Francesco Scala, Pietro H. Guzzi, Concetta Irace, Sergio Flesca, Pierangelo Veltri:
On the identification of PoIs in glucosimeter data. ICHI 2022: 542-544 - [c3]Sergio Flesca, Domenico Mandaglio, Francesco Scala, Andrea Tagarelli:
Learning to Active Learn by Gradient Variation based on Instance Importance. ICPR 2022: 2224-2230 - [c2]Francesco Scala, Stefano Mangini, Chiara Macchiavello, Daniele Bajoni, Dario Gerace:
Quantum variational learning for entanglement witnessing. IJCNN 2022: 1-8
2010 – 2019
- 2019
- [j1]Bettina Fazzinga, Sergio Flesca, Filippo Furfaro, Francesco Scala:
Efficiently computing extensions' probabilities over probabilistic Bipolar Abstract Argumentation Frameworks. Intelligenza Artificiale 13(2): 189-200 (2019) - 2018
- [c1]Bettina Fazzinga, Sergio Flesca, Filippo Furfaro, Francesco Scala:
Computing Extensions' Probabilities over Probabilistic Bipolar Abstract Argumentation Frameworks. AI³@AI*IA 2018: 57-70
Coauthor Index
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