PDaSP Track 3: Testbed for Enhancing Privacy and Robustness of Federated Learning Systems
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Traditional machine learning often involves collecting data from multiple sources, which can raise significant privacy concerns. One approach has emerged as a promising solution to solve this challenge by enabling models to be trained across many different sources without directly sharing private data. This approach has become particularly…
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