广东工业大学学报2025，Vol.42Issue(3)：1-11,11.DOI:10.12052/gdutxb.240118
云量子机器学习研究进展
Progress in Cloud-based Quantum Machine Learning
摘要
Abstract
With the rapid advancement of quantum computing and information technology,cloud-based quantum machine learning has emerged as a promising solution,enabling resource-constrained users to perform quantum machine learning tasks via remote quantum servers while ensuring privacy protection for both data and models.A relatively comprehensive overview of the latest developments in this field is provided,starting from the fundamental theories of quantum inner products and variational quantum algorithms.An analysis is conducted on the implementation details and application examples of various cloud-based quantum machine learning methods based on quantum inner products and cloud-based variational quantum algorithms.Additionally,the challenges faced by current technologies are discussed and insights into future research directions are offered.关键词
云量子机器学习/隐私保护/量子内积/变分量子算法Key words
cloud-based quantum machine learning/privacy protection/quantum inner product/variational quantum algorithms分类
计算机与自动化引用本文复制引用
杨俊鸿,王帮海,钟志..云量子机器学习研究进展[J].广东工业大学学报,2025,42(3):1-11,11.基金项目
国家自然科学基金资助项目(62072119) （62072119）
