18 citations · 19 across the 7 of their papers we have counts for
Showing 2023 · quant-phShow all
3 papers · 2 filters
quant-ph2023
Tuning Quantum Computing Privacy through Quantum Error Correction
Hui Zhong, Keyi Ju, Manojna Sistla +4
Quantum computing is a promising paradigm for efficiently solving large and high-complexity problems. To protect quantum computing privacy, pioneering research efforts proposed to…
quant-ph2023
Harnessing Inherent Noises for Privacy Preservation in Quantum Machine Learning
Keyi Ju, Xiaoqi Qin, Hui Zhong +3
Quantum computing revolutionizes the way of solving complex problems and handling vast datasets, which shows great potential to accelerate the machine learning process. However, da…
quant-ph2023
Differential Privacy Preserving Quantum Computing via Projection Operator Measurements
Yuqing Li, Yusheng Zhao, Xinyue Zhang +3
Quantum computing has been widely applied in various fields, such as quantum physics simulations, quantum machine learning, and big data analysis. However, in the domains of data-d…