MC^2-SF: Slow-Fast Learning for Mobile-Cloud Collaborative  Recommendation

The information explosion on the websites greatly drives the development of recommender systems, which automatically search the content. e.et al. et al. et al. (and (b). For the slow component deployed in the cloud, it enjoys the large computing power and the rich but delayed user behaviors, which drive the development of a range of deep-learning-based models like SASRec .

Link: MC^2-SF: Slow-Fast Learning for Mobile-Cloud Collaborative
Recommendation

via deepai.org

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