Federated Hyperparameter Tuning

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Questions and Answers

What is the main challenge in hyperparameter tuning in federated learning?

The need to keep data on device and perform local training makes it difficult to efficiently train and evaluate configurations.

What is the goal of federated hyperparameter tuning?

To optimize hyperparameters in a distributed network of heterogeneous devices.

How are models learned in federated learning?

Models are learned over a distributed network of heterogeneous devices.

What is the role of standard approaches in federated hyperparameter tuning?

<p>Standard approaches can be adapted to form baselines for the federated sett.</p> Signup and view all the answers

Why is hyperparameter optimization challenging in federated learning?

<p>The need to keep data on device and perform local training makes it difficult to efficiently train and evaluate configurations.</p> Signup and view all the answers

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