FedFast: Going Beyond Average for Faster Training of Federated Recommender Systems.
Khalil MuhammadQinqin WangDiarmuid O'Reilly-MorganElias Z. TragosBarry SmythNeil HurleyJames GeraciAonghus LawlorPublished in: KDD (2020)
Keyphrases
- recommender systems
- collaborative filtering
- training set
- matrix factorization
- user preferences
- user profiling
- digital libraries
- memory efficient
- user modeling
- training process
- missing data
- sentiment analysis
- test set
- training examples
- information filtering
- training phase
- user profiles
- training samples
- online learning