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cs.LG2022
Fair Effect Attribution in Parallel Online Experiments
Alexander Buchholz, Vito Bellini, Giuseppe Di Benedetto +3
A/B tests serve the purpose of reliably identifying the effect of changes introduced in online services. It is common for online platforms to run a large number of simultaneous exp…
cs.LG2020
Learning to Rank in the Position Based Model with Bandit Feedback
Beyza Ermis, Patrick Ernst, Yannik Stein +1
Personalization is a crucial aspect of many online experiences. In particular, content ranking is often a key component in delivering sophisticated personalization results. Commonl…