CaBaFL: Asynchronous Federated Learning via Hierarchical Cache and Feature Balance

no code implementations • 19 Apr 2024 • Zeke Xia, Ming Hu, Dengke Yan, Xiaofei Xie, Tianlin Li, Anran Li, Junlong Zhou, Mingsong Chen

To address the problem of imbalanced data, the feature balance-guided device selection strategy in CaBaFL adopts the activation distribution as a metric, which enables each intermediate model to be trained across devices with totally balanced data distributions before aggregation.

Federated Learning

Robust Median Reversion Strategy for On-Line Portfolio Selection

1 code implementation • Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence 2013 • Dingjiang Huang, Junlong Zhou, Bin Li, Steven C.H. Hoi, Shuigeng Zhou

Online portfolio selection has been attracting increasing interests from artificial intelligence community in recent decades.