3 papers
cs.LG2026
QSplitFL: Capability Aware Deep Q-Learning for Optimal Split Point Selection in Split Federated Learning
Nazmus Shakib Shadin, Xinyue Zhang, Jingyi Wang +1
Federated Learning (FL) combined with Split Learning (SL) is a privacy preserving paradigm that enables training deep neural networks (DNNs) on resource constrained devices while r…
quant-ph2025
Differential Privacy Preserving Distributed Quantum Computing
Hui Zhong, Keyi Ju, Jiachen Shen +5
Existing quantum computers can only operate with hundreds of qubits in the Noisy Intermediate-Scale Quantum (NISQ) state, while quantum distributed computing (QDC) is regarded as a…
quant-ph2024
Bridging Quantum Computing and Differential Privacy: Insights into Quantum Computing Privacy
Yusheng Zhao, Hui Zhong, Xinyue Zhang +3
While quantum computing has strong potential in data-driven fields, the privacy issue of sensitive or valuable information involved in the quantum algorithm should be considered. D…