Hi,
May I please check if model personalization algorithms are allowed for the competition? That is, instead of having a single shared FL model, can each participating client (federation unit, e.g. a bank) maintain its own customized model which is learned as part of the FL procedure?
Both tracks currently seem to suggest that the final solution should be a single “privacy-preserving federated model trained using your privacy solution” (e.g. Competition: PETs Prize Challenge: Phase 1); I wanted to confirm with you since there has been past research suggesting that model personalization can be significantly better than global methods (i.e. methods with a single shared model), particularly when the clients may be stateful.
Thanks!