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Ito Diffusion Approximation of Universal Ito Chains for Sampling, Optimization and Boosting.

, and . CoRR, (2023)

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On Gradient Boosted Decision Trees and Neural Rankers: A Case-Study on Short-Video Recommendations at ShareChat., , , , , , , , , and . FIRE, page 136-141. ACM, (2023)StochasticRank: Global Optimization of Scale-Free Discrete Functions., and . ICML, volume 119 of Proceedings of Machine Learning Research, page 9669-9679. PMLR, (2020)SGLB: Stochastic Gradient Langevin Boosting., and . CoRR, (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)Gradient Boosting Performs Low-Rank Gaussian Process Inference., , and . CoRR, (2022)Learning Metrics that Maximise Power for Accelerated A/B-Tests., and . CoRR, (2024)SGLB: Stochastic Gradient Langevin Boosting., and . ICML, volume 139 of Proceedings of Machine Learning Research, page 10487-10496. PMLR, (2021)