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FEL: High Capacity Learning for Recommendation and Ranking via Federated Ensemble Learning
[article]
2022
arXiv
pre-print
Federated learning (FL) has emerged as an effective approach to address consumer privacy needs. FL has been successfully applied to certain machine learning tasks, such as training smart keyboard models and keyword spotting. Despite FL's initial success, many important deep learning use cases, such as ranking and recommendation tasks, have been limited from on-device learning. One of the key challenges faced by practical FL adoption for DL-based ranking and recommendation is the prohibitive
arXiv:2206.03852v1
fatcat:dhcfj3jfrrh53doz3rryhgfwyi