Quantum Federated Learning for Image Classification

Sünkel, Leo; Altmann, Philipp ; Kölle, Michael und Gabor, Thomas (2024): Quantum Federated Learning for Image Classification. ICAART 2024: 16. Internationale Konferenz über Agenten und künstliche Intelligenz, Rom, Italien, 24. - 26. Februar 2024. Rocha, Ana Paula; Steels, Luc und Herik, Jaap van den (Hrsg.): In: Proceedings of the 16th International Conference on Agents and Artificial Intelligence, Bd. 3 Setúbal: SciTePress. S. 936-942

Abstract

Federated learning is a technique in classical machine learning in which a global model is collectively trained by a number of independent clients, each with their own datasets. Using this learning method, clients are not required to reveal their dataset as it remains local; clients may only exchange parameters with each other. As the interest in quantum computing and especially quantum machine learning is steadily increasing, more concepts and approaches based on classical machine learning principles are being applied to the respective counterparts in the quantum domain. Thus, the idea behind federated learning has been transferred to the quantum realm in recent years. In this paper, we evaluate a straightforward approach to quantum federated learning using the widely used MNIST dataset. In this approach, we replace a classical neural network with a variational quantum circuit, i.e., the global model as well as the clients are trainable quantum circuits. We run three different experiments which differ in number of clients and data-subsets used. Our results demonstrate that basic principles of federated learning can be applied to the quantum domain while still achieving acceptable results. However, they also illustrate that further research is required for scenarios with increasing number of clients.

• Dokumententyp: Konferenzbeitrag (Paper)
• Fakultät: Mathematik, Informatik und Statistik > Informatik > Künstliche Intelligenz und Maschinelles Lernen
• Themengebiete: 000 Informatik, Informationswissenschaft, allgemeine Werke > 004 Informatik
• ISBN: 978-989-758-680-4
• Ort: Setúbal
• Sprache: Englisch