| Quasi-monte carlo variational inference A Buchholz, F Wenzel, S Mandt International Conference on Machine Learning, 668-677, 2018 | 69 | 2018 |
| Adaptive tuning of hamiltonian monte carlo within sequential monte carlo A Buchholz, N Chopin, PE Jacob Bayesian Analysis 16 (3), 745-771, 2021 | 41 | 2021 |
| Improving approximate Bayesian computation via quasi-Monte Carlo A Buchholz, N Chopin Journal of Computational and Graphical Statistics 28 (1), 205-219, 2019 | 32 | 2019 |
| Low-variance estimation in the Plackett-Luce model via quasi-Monte Carlo sampling A Buchholz, JM Lichtenberg, G Di Benedetto, Y Stein, V Bellini, M Ruffini arXiv preprint arXiv:2205.06024, 2022 | 8 | 2022 |
| Distributed computation for marginal likelihood based model choice A Buchholz, D Ahfock, S Richardson Bayesian Analysis 18 (2), 607-638, 2023 | 7 | 2023 |
| Modeling position bias ranking for streaming media services M Ruffini, V Bellini, A Buchholz, G Di Benedetto, Y Stein Companion Proceedings of the Web Conference 2022, 72-76, 2022 | 7 | 2022 |
| Quasi-monte carlo flows F Wenzel, A Buchholz, S Mandt Proceedings of the 3rd Workshop on Bayesian Deep Learning, 2018 | 7 | 2018 |
| Contextual position bias estimation using a single stochastic logging policy G Di Benedetto, A Buchholz, B London, M Jakimov, Y Stein, ... | 4 | 2023 |
| Ranker-agnostic Contextual Position Bias Estimation O Barbany Mayor, V Bellini, A Buchholz, G Di Benedetto, DM Granziol, ... arXiv e-prints, arXiv: 2107.13327, 2021 | 3* | 2021 |
| Self-normalized off-policy estimators for ranking B London, A Buchholz, G Di Benedetto, JM Lichtenberg, Y Stein, ... | 2 | 2023 |
| Off-policy evaluation for learning-to-rank via interpolating the item-position model and the position-based model A Buchholz, B London, G Di Benedetto, T Joachims arXiv preprint arXiv:2210.09512, 2022 | 2 | 2022 |
| Counterfactual ranking evaluation with flexible click models A Buchholz, B London, G Di Benedetto, JM Lichtenberg, Y Stein, ... Proceedings of the 47th International ACM SIGIR Conference on Research and …, 2024 | 1 | 2024 |
| Double Clipping: Less-Biased Variance Reduction in Off-Policy Evaluation JM Lichtenberg, A Buchholz, G Di Benedetto, M Ruffini, B London arXiv preprint arXiv:2309.01120, 2023 | 1 | 2023 |
| Unbiased offline evaluation for learning to rank with business rules M Jakimov, A Buchholz, Y Stein, T Joachims | 1 | 2023 |
| Fair effect attribution in parallel online experiments A Buchholz, V Bellini, G Di Benedetto, Y Stein, M Ruffini, F Moerchen Companion Proceedings of the Web Conference 2022, 77-83, 2022 | 1 | 2022 |
| Large language models as recommender systems: A study of popularity bias JM Lichtenberg, A Buchholz, P Schwöbel arXiv preprint arXiv:2406.01285, 2024 | | 2024 |
| Data Study Group Final Report: Roche M Abdollahyan, I Bica, A Buchholz, S Conde, N Cunningham, J Dennis, ... Alan Turing Institute, 2020 | | 2020 |
| High dimensional Bayesian computation A Buchholz Université Paris-Saclay, 2018 | | 2018 |
| Hamiltonian Monte Carlo sampling for Wishart distributions with eigenvalue constraints A Buchholz, N Chopin, M Kloft, S Mandt | | 2016 |
| Extreme value analysis of speeding data A Buchholz Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät, 2013 | | 2013 |
Matteo RuffiniAmazonVerified email at amazon.com
