IEEE

Secure Aggregation With Logarithmic Overhead for Federated Learning in VANETs

Abstract: As a critical component in federated learning (FL), secure aggregation enables the server to learn the aggregated model without observing clients’ local training gradients. However, limited ...
IEEE

Toward Secure Weighted Aggregation for Privacy-Preserving Federated Learning

Abstract: Privacy-preserving federated learning can protect the privacy of model gradients/parameters in the model aggregation phase. Most existing schemes only ...
InfoQ

Hardwood Promises High-Speed JVM Apache Parquet Processing with Zero Mandatory Dependencies

Hardwood, the project Gunnar Morling kick-started handling of Parquet files in Java, reached version 1. Its multi-threaded approach and zero mandatory external dependencies promise a simpler, more ...