33 citations · 39 across the 8 of their papers we have counts for
4 papers · 1 filter
GuardFed: A Trustworthy Federated Learning Framework Against Dual-Facet Attacks
Yanli Li, Yanan Zhou, Zhongliang Guo +6
Federated learning (FL) enables privacy-preserving collaborative model training but remains vulnerable to adversarial behaviors that compromise model utility or fairness across sen…
Optimal Look-back Horizon for Time Series Forecasting in Federated Learning
Dahao Tang, Nan Yang, Yanli Li +3
Selecting an appropriate look-back horizon remains a fundamental challenge in time series forecasting (TSF), particularly in the federated learning scenarios where data is decentra…
Holistic Evaluation Metrics: Use Case Sensitive Evaluation Metrics for Federated Learning
Yanli Li, Jehad Ibrahim, Huaming Chen +2
A large number of federated learning (FL) algorithms have been proposed for different applications and from varying perspectives. However, the evaluation of such approaches often r…
Quantum-Enhanced Forecasting: Leveraging Quantum Gramian Angular Field and CNNs for Stock Return Predictions
Zhengmeng Xu, Yujie Wang, Xiaotong Feng +3
We propose a time series forecasting method named Quantum Gramian Angular Field (QGAF). This approach merges the advantages of quantum computing technology with deep learning, aimi…