| Uncertainty in Gradient Boosting via Ensembles A Malinin, L Prokhorenkova, A Ustimenko International Conference on Learning Representations, 2021, 2020 | 89 | 2020 |
| SGLB: Stochastic Gradient Langevin Boosting A Ustimenko, L Prokhorenkova International Conference on Machine Learning, 2021, 2020 | 25* | 2020 |
| StochasticRank: Global Optimization of Scale-Free Discrete Functions A Ustimenko, L Prokhorenkova International Conference on Machine Learning, 2020, 2020 | 17 | 2020 |
| Learning to select for a predefined ranking A Ustimenko, A Vorobev, G Gusev, P Serdyukov International Conference on Machine Learning, 6477-6486, 2019 | 7 | 2019 |
| On (Normalised) Discounted Cumulative Gain as an Offline Evaluation Metric for Top-𝑛 Recommendation O Jeunen, I Potapov, A Ustimenko arXiv preprint arXiv:2307.15053, 2023 | 5 | 2023 |
| Which Tricks are Important for Learning to Rank? I Lyzhin, A Ustimenko, A Gulin, L Prokhorenkova International Conference on Machine Learning, 2023, 2022 | 5 | 2022 |
| Method and server for training machine learning algorithm for ranking objects AI Ustimenko US Patent App. 17/223,680, 2021 | 4 | 2021 |
| Learning-to-Rank with Nested Feedback H Sagtani, O Jeunen, A Ustimenko European Conference on Information Retrieval, 306-315, 2024 | 1 | 2024 |
| Variance Reduction in Ratio Metrics for Efficient Online Experiments S Baweja, N Pokharna, A Ustimenko, O Jeunen European Conference on Information Retrieval, 292-297, 2024 | 1 | 2024 |
| On Gradient Boosted Decision Trees and Neural Rankers: A Case-Study on Short-Video Recommendations at ShareChat O Jeunen, H Sagtani, H Doi, R Karimov, N Pokharna, D Kalim, ... Proceedings of the 15th Annual Meeting of the Forum for Information …, 2023 | 1 | 2023 |
| Methods and systems for generating an uncertainty score for an output of a Gadient Boosting Decision Tree model LA Prokhorenkova, AI Ustimenko, AA Malinin US Patent App. 17/351,719, 2022 | 1 | 2022 |
| Gradient Boosting Performs Gaussian Process Inference A Ustimenko, A Beliakov, L Prokhorenkova International Conference on Learning Representations, 2023, 2022 | 1 | 2022 |
| Methods and systems for training a decision-tree based machine learning algorithm (mla) AI Ustimenko US Patent App. 17/207,403, 2022 | 1 | 2022 |
| The triviality condition for kernels of quadratic mappings and its application in optimization methods A Tret’yakov, E Tyrtyshnikov, A Ustimenko Russian Journal of Numerical Analysis and Mathematical Modelling 32 (4), 267-274, 2017 | 1 | 2017 |
| Learning Metrics that Maximise Power for Accelerated A/B-Tests O Jeunen, A Ustimenko arXiv preprint arXiv:2402.03915, 2024 | | 2024 |
| Ito Diffusion Approximation of Universal Ito Chains for Sampling, Optimization and Boosting A Ustimenko, A Beznosikov International Conference on Learning Representations, 2024, 2023 | | 2023 |
| Deep Stochastic Mechanics E Orlova, A Ustimenko, R Jiang, PY Lu, R Willett arXiv preprint arXiv:2305.19685, 2023 | | 2023 |
| Method of and system for ranking digital objects based on objective characteristic associated therewith AI Ustimenko, AL Vorobyev, GG Gusev, PV Serdyukov US Patent 11,308,099, 2022 | | 2022 |
| On Matrix Subspaces with Trivial Quadratic Kernels A Tret’yakov, E Tyrtyshnikov, A Ustimenko Structured Matrices in Numerical Linear Algebra 30 (Springer INdAM Series …, 2019 | | 2019 |
Liudmila Ostroumova ProkhorenkovaYandexVerified email at yandex-team.ru
