An efficient federated distillation learning system for multitask time series classification
H ** in DP‐SGD, empirically
G Lin, H Yan, G Kou, T Huang, S Peng… - … Journal of Intelligent …, 2022 - Wiley Online Library
Abstract Differentially Private Stochastic Gradient Descent (DP‐SGD) is a prime method for
training machine learning models with rigorous privacy guarantees. Since its birth, DP‐SGD …
training machine learning models with rigorous privacy guarantees. Since its birth, DP‐SGD …
Divide-and-conquer the NAS puzzle in resource-constrained federated learning systems
Federated Learning (FL) is a privacy-preserving distributed machine learning approach
geared towards applications in edge devices. However, the problem of designing custom …
geared towards applications in edge devices. However, the problem of designing custom …
Membership reconstruction attack in deep neural networks
To further enhance the reliability of Machine Learning (ML) systems, considerable efforts
have been dedicated to develo** privacy protection techniques. Recently, membership …
have been dedicated to develo** privacy protection techniques. Recently, membership …
Personalized federated learning for in-hospital mortality prediction of multi-center ICU
Federated learning (FL), as a paradigm for addressing challenges of machine learning (ML)
to be applied in private distributed data provides a novel and promising scheme to promote …
to be applied in private distributed data provides a novel and promising scheme to promote …
Towards Privacy-Preserving Federated Neuromorphic Learning via Spiking Neuron Models
B Han, Q Fu, X Zhang - Electronics, 2023 - mdpi.com
Federated learning (FL) has been broadly adopted in both academia and industry in recent
years. As a bridge to connect the so-called “data islands”, FL has contributed greatly to …
years. As a bridge to connect the so-called “data islands”, FL has contributed greatly to …