Harmony: Heterogeneity-aware hierarchical management for federated learning system
Federated learning (FL) enables multiple devices to collaboratively train a shared model
while preserving data privacy. However, despite its emerging applications in many areas …
while preserving data privacy. However, despite its emerging applications in many areas …
HARMONY: Heterogeneity-Aware Hierarchical Management for Federated Learning System
C Tian, L Li, Z Shi, J Wang, CZ Xu - 2022 55th IEEE/ACM …, 2022 - computer.org
Federated learning (FL) enables multiple devices to collaboratively train a shared model
while preserving data privacy. However, despite its emerging applications in many areas …
while preserving data privacy. However, despite its emerging applications in many areas …
HARMONY: Heterogeneity-Aware Hierarchical Management for Federated Learning System
C Tian, L Li, Z Shi, J Wang, CZ Xu - … of the 55th Annual IEEE/ACM …, 2022 - dl.acm.org
Federated learning (FL) enables multiple devices to collaboratively train a shared model
while preserving data privacy. However, despite its emerging applications in many areas …
while preserving data privacy. However, despite its emerging applications in many areas …
HARMONY: Heterogeneity-Aware Hierarchical Management for Federated Learning System
C Tian, L Li, Z Shi, J Wang, CZ Xu - 2022 - repository.um.edu.mo
Federated learning (FL) enables multiple devices to collaboratively train a shared model
while preserving data privacy. However, despite its emerging applications in many areas …
while preserving data privacy. However, despite its emerging applications in many areas …