Quantum computing meets federated learning

• 作者: Kaifeng Bu
• 来源期刊: 中国科学：物理学 力学 天文学（英文版）
• 年，卷（期）: 2022,（1）
• 所属期刊栏目: Research Highlight
• 页码范围: 119
• 页数: 1页
• 语种: 英文

摘要

Quantum machine leaming is an emerging interdisciplinary field that explores the interplay between machine leaming and quantum physics,holding the potential to revolutionize a number of aspects of artificial intelligence [1].Meanwhile,blind quantum computing (BQC) protocols,which are pro-posed for private quantum computation,promise to handle delegated computing tasks without revealing clients' private data [2].The combination of quantum machine learning and blind quantum computing may shed light on multiparty federated learning tasks.