Abstract: Expensive constrained multi-objective optimization problems (ECMOPs) present a significant challenge to surrogate-assisted evolutionary algorithms (SAEAs) in effectively balancing ...
Abstract: Federated Learning (FL) is an emerging computing paradigm to collaboratively train Machine Learning (ML) models across multi-source data while preserving privacy. The major challenge of ...
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