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QI: Fachverband Quanteninformation

QI 2: Quantum Machine Learning I

QI 2.2: Vortrag

Montag, 10. März 2025, 11:15–11:30, HS VIII

Automation of Quantum Machine Learning — •Marco Roth — Fraunhofer IPA, Stuttgart

Applying quantum machine learning (QML) presents unique challenges that often demand expertise in fields such as machine learning and quantum computing. To address these challenges and facilitate broader applications, automation offers a promising solution. In this talk, we introduce two approaches that leverage this concept. The first is AutoQML, a framework designed to create end-to-end QML pipelines for a range of supervised learning scenarios, including time series classification and tabular regression and classification tasks. Additionally, we propose a novel method that employs reinforcement learning techniques to develop problem-specific encoding circuits, enhancing the performance of QML models in a sample-efficient way.

Keywords: Quantum Machine Learning; Quantum Computing; Quantum Computing Algorithms