Alexander Buchholz

According to our database, Alexander Buchholz authored at least 9 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Unbiased Offline Evaluation for Learning to Rank with Business Rules.

Matej Jakimov, Alexander Buchholz, Yannik Stein, Thorsten Joachims

CoRR, 2023

Double Clipping: Less-Biased Variance Reduction in Off-Policy Evaluation.

Jan Malte Lichtenberg, Alexander Buchholz, Giuseppe Di Benedetto, Matteo Ruffini, Ben London

CoRR, 2023

Contextual Position Bias Estimation Using a Single Stochastic Logging Policy.

Giuseppe Di Benedetto, Alexander Buchholz, Ben London, Matej Jakimov, Yannik Stein, Jan Malte Lichtenberg, Vito Bellini, Matteo Ruffini, Thorsten Joachims

Proceedings of the Workshop on Learning and Evaluating Recommendations with Impressions co-located with the 17th ACM Conference on Recommender Systems (RecSys 2023), 2023

2022

Off-policy evaluation for learning-to-rank via interpolating the item-position model and the position-based model.

Alexander Buchholz, Ben London, Giuseppe Di Benedetto, Thorsten Joachims

CoRR, 2022

Low-variance estimation in the Plackett-Luce model via quasi-Monte Carlo sampling.

Alexander Buchholz, Jan Malte Lichtenberg, Giuseppe Di Benedetto, Yannik Stein, Vito Bellini, Matteo Ruffini

CoRR, 2022

Modeling Position Bias Ranking for Streaming Media Services.

Matteo Ruffini, Vito Bellini, Alexander Buchholz, Giuseppe Di Benedetto, Yannik Stein

Proceedings of the Companion of The Web Conference 2022, Virtual Event / Lyon, France, April 25, 2022

Fair Effect Attribution in Parallel Online Experiments.

Alexander Buchholz, Vito Bellini, Giuseppe Di Benedetto, Yannik Stein, Matteo Ruffini, Fabian Moerchen

Proceedings of the Companion of The Web Conference 2022, Virtual Event / Lyon, France, April 25, 2022

2021

Ranker-agnostic Contextual Position Bias Estimation.

Oriol Barbany Mayor, Vito Bellini, Alexander Buchholz, Giuseppe Di Benedetto, Diego Marco Granziol, Matteo Ruffini, Yannik Stein

CoRR, 2021

2018

Quasi-Monte Carlo Variational Inference.

Alexander Buchholz, Florian Wenzel, Stephan Mandt

Proceedings of the 35th International Conference on Machine Learning, 2018