2 papers
cs.IR2023
FedFNN: Faster Training Convergence Through Update Predictions in Federated Recommender Systems
Francesco Fabbri, Xianghang Liu, Jack R. McKenzie +2
Federated Learning (FL) has emerged as a key approach for distributed machine learning, enhancing online personalization while ensuring user data privacy. Instead of sending privat…
stat.ML2020
Fast Approximate Bayesian Contextual Cold Start Learning (FAB-COST)
Jack R. McKenzie, Peter A. Appleby, Thomas House +1
Cold-start is a notoriously difficult problem which can occur in recommendation systems, and arises when there is insufficient information to draw inferences for users or items. To…