Introduces C-MOPPO algorithm that converts inference requests to training data via tandem queues, incorporates data/model freshness, and uses constrained multi-objective RL to optimize mode selection and resource allocation in federated edge learning.
Federated learning with noisy user feedback,
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2026 1verdicts
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Joint Optimization of Training and Inference in Federated Edge Learning via Constrained Multi-Objective Deep Reinforcement Learning
Introduces C-MOPPO algorithm that converts inference requests to training data via tandem queues, incorporates data/model freshness, and uses constrained multi-objective RL to optimize mode selection and resource allocation in federated edge learning.