Federated learning-based natural language processing: a systematic literature review
Younas Khan,
David Sánchez,
Josep Domingo-Ferrer
Abstract:Federated learning (FL) is a decentralized machine learning (ML) framework that allows models to be trained without sharing the participants’ local data. FL thus preserves privacy better than centralized machine learning. Since textual data (such as clinical records, posts in social networks, or search queries) often contain personal information, many natural language processing (NLP) tasks dealing with such data have shifted from the centralized to the FL setting. However, FL is not free from issues, includin… Show more
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