9 citations · 27 across the 10 of their papers we have counts for
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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…
stat.ML2022★ 1 cited
Low-variance estimation in the Plackett-Luce model via quasi-Monte Carlo sampling
Alexander Buchholz, Jan Malte Lichtenberg, Giuseppe Di Benedetto +3
The Plackett-Luce (PL) model is ubiquitous in learning-to-rank (LTR) because it provides a useful and intuitive probabilistic model for sampling ranked lists. Counterfactual offlin…