FedFNN: Faster Training Convergence Through Update Predictions in Federated Recommender Systems.
Francesco FabbriXianghang LiuJack R. McKenzieBartlomiej TwardowskiTri Kurniawan WijayaPublished in: CoRR (2023)
Keyphrases
- recommender systems
- training phase
- collaborative filtering
- faster convergence
- training set
- matrix factorization
- training process
- user profiling
- online learning
- personalized recommendation
- neural network
- convergence rate
- user profiles
- training samples
- supervised learning
- digital libraries
- user ratings
- user model
- stochastic gradient descent
- update rule
- collaborative filtering recommender systems
- information overload
- training algorithm
- information filtering
- convergence speed
- test set
- data sources
- e learning
- search engine
- genetic algorithm