Abstract: Federated learning (FL), as a promising machine learning paradigm for large-scale distributed data, faces two security challenges of privacy and robustness: the transmitted model updates ...
This study presents valuable findings implicating nuclear export in the regulation of protein condensate behaviour and TDP-43 phase behaviour, suggesting a link to pathogenic aggregation in ALS/FTD.
Abstract: Federated learning (FL) is a privacy-preserving alternative to centralized machine learning, where model training is performed on local devices and only global model updates are shared, ...
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