Multitask Learning Insights
Virginia discusses the limitations of training a single model across a federated network, emphasizing the advantages of multitask learning. By treating each device as its own learning task, this approach allows for better personalization of models to local data. The simplicity of multitask learning can significantly enhance both fairness and robustness without complicating the learning objectives.In this clip
From this podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Fairness and Robustness in Federated Learning with Virginia Smith - #504
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