arXiv · 2305.18305
High Accuracy and Low Regret for User-Cold-Start Using Latent Bandits
Abstract
We develop a novel latent-bandit algorithm for tackling the cold-start problem for new users joining a recommender system. This new algorithm significantly outperforms the state of the art, simultaneously achieving both higher accuracy and lower regret.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
David Young, Douglas Leith. 2023-05-12. High Accuracy and Low Regret for User-Cold-Start Using Latent Bandits. https://doi.org/10.14428/esann%2F2022.es2022-79
Cite the original work for its findings. Save a collection to share your selection of sources.