pvFed: Personalized Vertical Federated learning for Client‐Specific Tasks
Akihito Nishikawa,
Tomu Yanabe,
Yuiko Sakuma
et al.
Abstract:Federated Learning (FL) is a distributed machine learning paradigm that enables multiple data holders to collaborate on building machine learning models while preserving the privacy of their data. FL can be categorized as horizontal or vertical, depending on the distribution characteristics of the data. Specifically, horizontal FL uses data partitioned in the sample space, whereas vertical FL uses data partitioned in the feature space. Traditional vertical FL methods aim to facilitate collaboration among clien… Show more
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