Abstract: The federated learning (FL) client selection scheme can effectively mitigate global model performance degradation caused by the random aggregation of clients with heterogeneous data.
An MDP-Driven Learning Function Selection Strategy for Kriging-Based Structural Reliability Analysis
Abstract: Active learning Kriging is widely used in structural reliability analysis for its computational efficiency and accuracy. While numerous learning functions exist to accelerate Kriging ...
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