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Found 3 papers, 3 papers with code
MDA: Availability-Aware Federated Learning Client Selection
Since many devices may be unavailable in cross-device FL, and communication between the server and all clients is extremely costly, only a fraction of clients gets selected for training at each round.
Towards Understanding Quality Challenges of the Federated Learning for Neural Networks: A First Look from the Lens of Robustness
Therefore, to better understand the current quality status and challenges of these SOTA FL techniques in the presence of attacks and faults, we perform a large-scale empirical study to investigate the SOTA FL's quality from multiple angles of attacks, simulated faults (via mutation operators), and aggregation (defense) methods.
Robustness Analysis of Deep Learning Frameworks on Mobile Platforms
This requires frameworks to execute machine learning models (e. g., Deep Neural Networks) on mobile devices.
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