Mugon Joe

Fed-ADE: Adaptive Learning Rate for Federated Post-adaptation under Distribution Shift

Federated learning (FL) in post-deployment settings must adapt to non-stationary data streams across heterogeneous clients without access to ground-truth labels. A major challenge is learning rate selection under client-specific, time-varying distribution shifts, where fixed learning rates often lea