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FedMQ+: Towards efficient heterogeneous federated learning with multi-grained quantization
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ReferencesShowing 10 of 29 papersPersonalized Meta-Federated Learning for IoT-Enabled Health Monitoring. PervasiveFL: Pervasive Federated Learning for Heterogeneous IoT Systems Differentially Private Low-Rank Adaptation of Large Language Model Using Federated Learning Sparse Communication for Distributed Gradient Descent Client Scheduling and Resource Management for Efficient Training in Heterogeneous IoT-Edge Federated Learning FedQMIX: Communication-efficient federated learning via multi-agent reinforcement learning Trustworthy decentralized collaborative learning for edge intelligence: A survey Advances and Open Problems in Federated Learning A survey of federated learning for edge computing: Research problems and solutions LQ-Nets: Learned Quantization for Highly Accurate and Compact Deep Neural Networks
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