Uncertainty in Gradient Boosting via Ensembles A Ustimenko, L Prokhorenkova, A Malinin ICLR 2021; arXiv preprint arXiv:2006.10562, 2020 | 40* | 2020 |
SGLB: Stochastic Gradient Langevin Boosting A Ustimenko, L Prokhorenkova ICML 2021; arXiv preprint arXiv:2001.07248, 2020 | 17* | 2020 |
StochasticRank: Global Optimization of Scale-Free Discrete Functions A Ustimenko, L Prokhorenkova International Conference on Machine Learning, 2020 | 10 | 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 |
Methods and systems for training a decision-tree based machine learning algorithm (mla) AI Ustimenko US Patent App. 17/207,403, 2022 | 1 | 2022 |
Method and server for training machine learning algorithm for ranking objects AI Ustimenko US Patent App. 17/223,680, 2021 | 1 | 2021 |
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 |
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 | | 2022 |
Gradient Boosting Performs Gaussian Process Inference A Ustimenko, A Beliakov, L Prokhorenkova ICLR 2023, 2022 | | 2022 |
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 |
Which Tricks are Important for Learning to Rank? I Lyzhin, A Ustimenko, A Gulin, L Prokhorenkova arXiv preprint arXiv:2204.01500, 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 |