Abstract: Hierarchical federated learning shows excellent potential for communication-computation trade-offs and reliable data privacy protection by introducing edge-cloud collaboration. Considering ...
Abstract: Privacy-preserving federated learning can protect the privacy of model gradients/parameters in the model aggregation phase. Most existing schemes only ...
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A Java-based performance testing framework and knowledge base engine. This project implements a fully functional, self-balancing AVL Tree from scratch to manage and query a generative AI dataset. The ...
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