Aleksei Ustimenko

32 papers A* 10A 3Journal 16Unranked 3
YearRankTypeTitle / Venue / Authors
2025 J jnl
Benchmarking Simulacra AI's Quantum Accurate Synthetic Data Generation for Chemical Sciences.
CoRR
Fabio Falcioni, Elena Orlova, Timothy Heightman, Philip Mantrov, Aleksei Ustimenko
2024 A* conf
Deep Stochastic Mechanics.
ICML
Elena Orlova, Aleksei Ustimenko, Ruoxi Jiang, Peter Y. Lu, Rebecca Willett
2024 A* conf
Ito Diffusion Approximation of Universal Ito Chains for Sampling, Optimization and Boosting.
ICLR
Aleksei Ustimenko, Aleksandr Beznosikov
2024 A* conf
Learning Metrics that Maximise Power for Accelerated A/B-Tests.
KDD
Olivier Jeunen, Aleksei Ustimenko
2024 J jnl
Learning Metrics that Maximise Power for Accelerated A/B-Tests.
CoRR
Olivier Jeunen, Aleksei Ustimenko
2024 — conf
Learning-to-Rank with Nested Feedback.
ECIR (3)
Hitesh Sagtani, Olivier Jeunen, Aleksei Ustimenko
2024 J jnl
Learning-to-Rank with Nested Feedback.
CoRR
Hitesh Sagtani, Olivier Jeunen, Aleksei Ustimenko
2024 A conf
Multi-Objective Recommendation via Multivariate Policy Learning.
RecSys
Olivier Jeunen, Jatin Mandav, Ivan Potapov, Nakul Agarwal, Sourabh Vaid, Wenzhe Shi, Aleksei Ustimenko
2024 J jnl
Multi-Objective Recommendation via Multivariate Policy Learning.
CoRR
Olivier Jeunen, Jatin Mandav, Ivan Potapov, Nakul Agarwal, Sourabh Vaid, Wenzhe Shi, Aleksei Ustimenko
2024 A* conf
On (Normalised) Discounted Cumulative Gain as an Off-Policy Evaluation Metric for Top-
KDD
Olivier Jeunen, Ivan Potapov, Aleksei Ustimenko
2024 A conf
Powerful A/B-Testing Metrics and Where to Find Them.
RecSys
Olivier Jeunen, Shubham Baweja, Neeti Pokharna, Aleksei Ustimenko
2024 J jnl
Powerful A/B-Testing Metrics and Where to Find Them.
CoRR
Olivier Jeunen, Shubham Baweja, Neeti Pokharna, Aleksei Ustimenko
2024 — conf
Variance Reduction in Ratio Metrics for Efficient Online Experiments.
ECIR (5)
Shubham Baweja, Neeti Pokharna, Aleksei Ustimenko, Olivier Jeunen
2024 J jnl
Variance Reduction in Ratio Metrics for Efficient Online Experiments.
CoRR
Shubham Baweja, Neeti Pokharna, Aleksei Ustimenko, Olivier Jeunen
2024 A conf
Δ-OPE: Off-Policy Estimation with Pairs of Policies.
RecSys
Olivier Jeunen, Aleksei Ustimenko
2024 J jnl
Δ-OPE: Off-Policy Estimation with Pairs of Policies.
CoRR
Olivier Jeunen, Aleksei Ustimenko
2023 J jnl
Deep Stochastic Mechanics.
CoRR
Elena Orlova, Aleksei Ustimenko, Ruoxi Jiang, Peter Y. Lu, Rebecca Willett
2023 A* conf
Gradient Boosting Performs Gaussian Process Inference.
ICLR
Aleksei Ustimenko, Artem Beliakov, Liudmila Prokhorenkova
2023 J jnl
Ito Diffusion Approximation of Universal Ito Chains for Sampling, Optimization and Boosting.
CoRR
Aleksei Ustimenko, Aleksandr Beznosikov
2023 J jnl
On (Normalised) Discounted Cumulative Gain as an Offline Evaluation Metric for Top-n Recommendation.
CoRR
Olivier Jeunen, Ivan Potapov, Aleksei Ustimenko
2023 — conf
On Gradient Boosted Decision Trees and Neural Rankers: A Case-Study on Short-Video Recommendations at ShareChat.
FIRE
Olivier Jeunen, Hitesh Sagtani, Himanshu Doi, Rasul Karimov, Neeti Pokharna, Md. Danish Kalim, Aleksei Ustimenko, Christopher Green, Rishabh Mehrotra, Wenzhe Shi
2023 J jnl
On Gradient Boosted Decision Trees and Neural Rankers: A Case-Study on Short-Video Recommendations at ShareChat.
CoRR
Olivier Jeunen, Hitesh Sagtani, Himanshu Doi, Rasul Karimov, Neeti Pokharna, Md. Danish Kalim, Aleksei Ustimenko, Christopher Green, Wenzhe Shi, Rishabh Mehrotra
2023 A* conf
Which Tricks are Important for Learning to Rank?
ICML
Ivan Lyzhin, Aleksei Ustimenko, Andrey Gulin, Liudmila Prokhorenkova
2022 J jnl
Gradient Boosting Performs Low-Rank Gaussian Process Inference.
CoRR
Aleksei Ustimenko, Artem Beliakov, Liudmila Prokhorenkova
2022 J jnl
Which Tricks are Important for Learning to Rank?
CoRR
Ivan Lyzhin, Aleksei Ustimenko, Andrey Gulin, Liudmila Prokhorenkova
2021 A* conf
SGLB: Stochastic Gradient Langevin Boosting.
ICML
Aleksei Ustimenko, Liudmila Prokhorenkova
2021 A* conf
Uncertainty in Gradient Boosting via Ensembles.
ICLR
Andrey Malinin, Liudmila Prokhorenkova, Aleksei Ustimenko
2020 J jnl
SGLB: Stochastic Gradient Langevin Boosting.
CoRR
Aleksei Ustimenko, Liudmila Prokhorenkova
2020 A* conf
StochasticRank: Global Optimization of Scale-Free Discrete Functions.
ICML
Aleksei Ustimenko, Liudmila Prokhorenkova
2020 J jnl
StochasticRank: Global Optimization of Scale-Free Discrete Functions.
CoRR
Aleksei Ustimenko, Liudmila Prokhorenkova
2020 J jnl
Uncertainty in Gradient Boosting via Ensembles.
CoRR
Aleksei Ustimenko, Liudmila Prokhorenkova, Andrey Malinin
2019 A* conf
Learning to select for a predefined ranking.
ICML
Aleksandr Vorobev, Aleksei Ustimenko, Gleb Gusev, Pavel Serdyukov