5 citations · 13 across the 9 of their papers we have counts for
4 papers · 1 filter
Scalable Quantum Neural Networks for Classification
Jindi Wu, Zeyi Tao, Qun Li
Many recent machine learning tasks resort to quantum computing to improve classification accuracy and training efficiency by taking advantage of quantum mechanics, known as quantum…
MUD-PQFed: Towards Malicious User Detection in Privacy-Preserving Quantized Federated Learning
Hua Ma, Qun Li, Yifeng Zheng +5
Federated Learning (FL), a distributed machine learning paradigm, has been adapted to mitigate privacy concerns for customers. Despite their appeal, there are various inference att…
LAWS: Look Around and Warm-Start Natural Gradient Descent for Quantum Neural Networks
Zeyi Tao, Jindi Wu, Qi Xia +1
Variational quantum algorithms (VQAs) have recently received significant attention from the research community due to their promising performance in Noisy Intermediate-Scale Quantu…
Towards Privacy-Preserving and Verifiable Federated Matrix Factorization
Xicheng Wan, Yifeng Zheng, Qun Li +3
Recent years have witnessed the rapid growth of federated learning (FL), an emerging privacy-aware machine learning paradigm that allows collaborative learning over isolated datase…