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Variance Reduction in Ratio Metrics for Efficient Online Experiments.

, , , and . ECIR (5), volume 14612 of Lecture Notes in Computer Science, page 292-297. Springer, (2024)

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StochasticRank: Global Optimization of Scale-Free Discrete Functions., and . ICML, volume 119 of Proceedings of Machine Learning Research, page 9669-9679. PMLR, (2020)Ito Diffusion Approximation of Universal Ito Chains for Sampling, Optimization and Boosting., and . CoRR, (2023)Uncertainty in Gradient Boosting via Ensembles., , and . ICLR, OpenReview.net, (2021)Which Tricks are Important for Learning to Rank?, , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 23264-23278. PMLR, (2023)Learning-to-Rank with Nested Feedback., , and . ECIR (3), volume 14610 of Lecture Notes in Computer Science, page 306-315. Springer, (2024)Learning to select for a predefined ranking., , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 6477-6486. PMLR, (2019)Δ-OPE: Off-Policy Estimation with Pairs of Policies., and . CoRR, (2024)Variance Reduction in Ratio Metrics for Efficient Online Experiments., , , and . ECIR (5), volume 14612 of Lecture Notes in Computer Science, page 292-297. Springer, (2024)SGLB: Stochastic Gradient Langevin Boosting., and . ICML, volume 139 of Proceedings of Machine Learning Research, page 10487-10496. PMLR, (2021)Gradient Boosting Performs Gaussian Process Inference., , and . ICLR, OpenReview.net, (2023)