Publikationen

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Antonio Macaluso; Luca Clissa; Stefano Lodi; Claudio Sartori
An efficient quantum algorithm for ensemble classification using bagging
In: IET Quantum Communication, Vol. 1, Pages 1-16, Wiley, 1/2024.
Antonio Macaluso
Quantum Supervised Learning
In: KI - Künstliche Intelligenz, German Journal on Artificial Intelligence - Organ des Fachbereiches "Künstliche Intelligenz" der Gesellschaft für Informatik e.V. (KI), Vol. 1, Pages 1-15, Springer, 2024.
Matteo Antonio Inajetovic; Filippo Orazi; Antonio Macaluso; Stefano Lodi; Claudio Sartori
Enabling Non-linear Quantum Operations Through Variational Quantum Splines
In: CCS 2023 Conference Proceedings. International Conference on Computational Science (ICCS-2023), July 3-5, Prague, Czech Republic, Pages 177-192, Vol. 10477, ISBN 978-3-031-36030-5, Springer, 7/2023.
Antonio Macaluso; Matthias Klusch; Stefano Lodi; Claudio Sartori
MAQA: A Quantum Framework for Supervised Learning
In: Quantum Information Processing (QIP), Vol. 22, Pages X-X, Springer Nature, 2023.
Supreeth Venkatesh; Antonio Macaluso; Matthias Klusch
GCS-Q: Quantum Graph Coalition Structure Generation
In: ICCS 2023 Conference Proceedings. International Conference on Computational Science (ICCS-2023), July 3-5, Prague, Czech Republic, Springer, 2023.
Supreeth Mysore Venkatesh; Antonio Macaluso; Marlon Nuske; Matthias Klusch; Andreas Dengel
Q-seg: Quantum annealing-based unsupervised image segmentation
In: ArXiv e-prints (arxiv), Vol. arXiv:2311.12912, Pages 1-8, arXiv, 2023.
Supreeth Venkatesh; Antonio Macaluso; Matthias Klusch
BILP-Q: Quantum Coalition Structure Generation
In: Proceedings of 19th ACM International Conference on Computing Frontiers. ACM International Conference on Computing Frontiers (CF-2022), May 17-19, Turin, Italy, ACM, 2022.
Antonio Macaluso; Filippo Orazi; Matthias Klusch; Stefano Lodi; Claudio Sartori
A Variational Algorithm for Quantum Single Layer Perceptron
In: Proceedings of 8th International Conference on Machine Learning, Optimization, and Data Science (LOD). Machine Learning, Optimization, and Data Science (LOD-2022), Springer Nature, 2022.