Chapter 17: Introduction to quantum federated machine learning
Samuel Yen-Chi Chen; Shinjae Yoo Brookhaven National Laboratory, Upton, NY, United States
Abstract
Recent advances in both quantum computing and machine learning have focused significant attention on efforts to combine these two fascinating technologies. The quantum machine learning (QML) field encompasses developing machine learning algorithms that run on quantum computers. Issues of concern for classical machine learning, such as privacy-preserving features and distributed training, remain important in the quantum world. For example, how can training be distributed across multiple quantum computers while ensuring data security and keeping model performance, such as classification ...
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