Drift-Aware Adaptive Aggregation (DAA) for federated learning on CIFAR-10 under heterogeneous client partitions.
-
Updated
Mar 15, 2026 - Python
Drift-Aware Adaptive Aggregation (DAA) for federated learning on CIFAR-10 under heterogeneous client partitions.
A parameter-transfer framework for generalized semiparametric models using model aggregation techniques.
Geometry dynamics and instability in federated LoRA under heterogeneous data distributions (FedGeoX)
Aggregation Tools for Matrix Population Models in R.
Data-Enhanced Model Aggregation
Add a description, image, and links to the model-aggregation topic page so that developers can more easily learn about it.
To associate your repository with the model-aggregation topic, visit your repo's landing page and select "manage topics."