From the 1 of 7 linked papers with an AI index.
7 papers
Accelerating A/B-Tests with Counterfactual Estimation: Reducing Variance through Policy Overlap
Olivier Jeunen
The paper introduces a new A/B‑testing protocol that uses counterfactual off‑policy estimation to exploit overlap between treatment and control policies, reducing variance and spee…
Auditing Marketing Budget Allocation with Hindsight Regret
Nilavra Pathak, Olivier Jeunen, Eric Lambert
Organizations routinely make strategic budget allocations under operational constraints, but often lack a principled way to assess whether realized allocations were close to the be…
Additive Control Variates Dominate Self-Normalisation in Off-Policy Evaluation
Olivier Jeunen, Shashank Gupta
Off-policy evaluation (OPE) is essential for assessing ranking and recommendation systems without costly online interventions. Self-Normalised Inverse Propensity Scoring (SNIPS) is…
Sustained Impact of Agentic Personalisation in Marketing: A Longitudinal Case Study
Olivier Jeunen, Eleanor Hanna, Schaun Wheeler
In consumer applications, Customer Relationship Management (CRM) has traditionally relied on the manual optimisation of static, rule-based messaging strategies. While adaptive and…
Unifying On- and Off-Policy Variance Reduction Methods
Olivier Jeunen
Continuous and efficient experimentation is key to the practical success of user-facing applications on the web, both through online A/B-tests and off-policy evaluation. Despite th…
-Testing the Waters: Empirically Validating Assumptions for Reliable A/B-Testing
Olivier Jeunen
A/B-tests are a cornerstone of experimental design on the web, with wide-ranging applications and use-cases. The statistical -test comparing differences in means is the most com…