23 citations · 82 across the 29 of their papers we have counts for
3 papers · 2 filters
Learning from Bandit Feedback: An Overview of the State-of-the-art
Olivier Jeunen, Dmytro Mykhaylov, David Rohde +3
In machine learning we often try to optimise a decision rule that would have worked well over a historical dataset; this is the so called empirical risk minimisation principle. In…
On the Value of Bandit Feedback for Offline Recommender System Evaluation
Olivier Jeunen, David Rohde, Flavian Vasile
In academic literature, recommender systems are often evaluated on the task of next-item prediction. The procedure aims to give an answer to the question: "Given the natural sequen…
Three Methods for Training on Bandit Feedback
Dmytro Mykhaylov, David Rohde, Flavian Vasile +2
There are three quite distinct ways to train a machine learning model on recommender system logs. The first method is to model the reward prediction for each possible recommendatio…