4 citations · 5 across the 3 of their papers we have counts for
4 papers
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…
Ranker-agnostic Contextual Position Bias Estimation
Oriol Barbany Mayor, Vito Bellini, Alexander Buchholz +4
Learning-to-rank (LTR) algorithms are ubiquitous and necessary to explore the extensive catalogs of media providers. To avoid the user examining all the results, its preferences ar…
A Linear Bandit for Seasonal Environments
Giuseppe Di Benedetto, Vito Bellini, Giovanni Zappella
Contextual bandit algorithms are extremely popular and widely used in recommendation systems to provide online personalised recommendations. A recurrent assumption is the stationar…
Non-exchangeable random partition models for microclustering
Giuseppe Di Benedetto, François Caron, Yee Whye Teh
Many popular random partition models, such as the Chinese restaurant process and its two-parameter extension, fall in the class of exchangeable random partitions, and have found wi…