Search Results for author:
Found 3 papers, 0 papers with code
Towards a Technical Debt for Recommender System
Balancing the management of technical debt within recommender systems requires effectively juggling the introduction of new features with the ongoing maintenance and enhancement of the current system.
Adversarial Sleeping Bandit Problems with Multiple Plays: Algorithm and Ranking Application
This paper presents an efficient algorithm to solve the sleeping bandit with multiple plays problem in the context of an online recommendation system.
Personalised novel and explainable matrix factorisation
In this paper, to the best of our knowledge, we propose a new model, denoted as NEMF, that allows to trade-off the MF performance with respect to the criteria of novelty and explainability, while only minimally compromising on accuracy.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
