1 citations · 2 across the 3 of their papers we have counts for
3 papers
Offline Recommender System Evaluation under Unobserved Confounding
Olivier Jeunen, Ben London
Off-Policy Estimation (OPE) methods allow us to learn and evaluate decision-making policies from logged data. This makes them an attractive choice for the offline evaluation of rec…
Double Clipping: Less-Biased Variance Reduction in Off-Policy Evaluation
Jan Malte Lichtenberg, Alexander Buchholz, Giuseppe Di Benedetto +2
"Clipping" (a.k.a. importance weight truncation) is a widely used variance-reduction technique for counterfactual off-policy estimators. Like other variance-reduction techniques, c…
Practical Bandits: An Industry Perspective
Bram van den Akker, Olivier Jeunen, Ying Li +3
The bandit paradigm provides a unified modeling framework for problems that require decision-making under uncertainty. Because many business metrics can be viewed as rewards (a.k.a…