@inproceedings{burlakov2026tfmctsqo,
title = {Practical Training-Free MCTS Query Optimization},
author = {Vladimir Burlakov and Alena Rybakina and Sergey Kudashev and Konstantin Gilev and Alexander Demin and Denis Ponomaryov and Yuriy Dorn},
booktitle = {arXiv},
year = {2026},
url = {https://arxiv.org/abs/2603.16474}
}
Training-Free Query Optimization via LLM-Based Plan Similarity
@inproceedings{vasilenko2026planmapping,
title = {Training-Free Query Optimization via LLM-Based Plan Similarity},
author = {Nikita Vasilenko and Alexander Demin and Vladimir Burlakov},
booktitle = {The Bulletin of Irkutsk State University. Series Mathematics},
year = {2026},
doi = {10.26516/1997-7670.2026.56.113},
url = {https://arxiv.org/abs/2506.05853}
}
Functional multi-armed bandit and the best function identification problems
@inproceedings{dorn2026functional,
title = {Functional multi-armed bandit and the best function identification problems},
author = {Yuriy Dorn and Aleksandr Katrutsa and Ilgam Latypov and Anastasiia Soboleva},
booktitle = {AAMAS 2026},
year = {2026},
doi = {10.65109/SFMN9947},
url = {https://arxiv.org/abs/2503.00509}
}
Robust autobidding for noisy conversion prediction models
@inproceedings{pudovikov2026robust,
title = {Robust autobidding for noisy conversion prediction models},
author = {Andrey Pudovikov and Aleksandra Khirianova and Ekaterina Solodneva and Gleb Molodtsov and Aleksandr Katrutsa and Yuriy Dorn and Egor Samosvat},
booktitle = {AAMAS 2026},
year = {2026},
doi = {10.65109/RXYW3025},
url = {https://arxiv.org/abs/2510.08788}
}
VK-LSVD: A Large-Scale Industrial Dataset for Short-Video Recommendation
@inproceedings{poplavsky2026vk,
title = {VK-LSVD: A Large-Scale Industrial Dataset for Short-Video Recommendation},
author = {Alexander Poplavsky and Alexander D'yakonov and Yuriy Dorn and Andrey Zimovnov},
booktitle = {Proceedings of the ACM Web Conference 2026},
year = {2026},
doi = {10.1145/3774904.3792933},
url = {https://arxiv.org/abs/2602.04567}
}
Uncertainty Quantification of Click and Conversion Estimates for the Autobidding
@inproceedings{zhigalskii2026uncertanty,
title = {Uncertainty Quantification of Click and Conversion Estimates for the Autobidding},
author = {Ivan Zhigalskii and Andrey Pudovikov and Aleksandr Katrutsa and Egor Samosvat},
booktitle = {arXiv},
year = {2026},
url = {https://arxiv.org/abs/2603.01825}
}
This review provides an overview of contemporary algorithms for smooth, multivariate optimization that utilize only information about the order of the function values, rather than their numerical magnitudes.
Survey of Modern Smooth Optimization Algorithms with Comparison Oracle
@inproceedings{lobanov2026smooth,
title = {Survey of Modern Smooth Optimization Algorithms with Comparison Oracle},
author = {Aleksandr Lobanov and Alexander Gasnikov},
booktitle = {Doklady Mathematics},
year = {2026},
doi = {10.7868/S3034504925060036}
}
We propose gradient-free algorithms with zeroth-order oracle under adversarial noise with unbounded variance, for non-smooth convex and convex-concave optimization problems.
Zeroth-order methods for non-smooth stochastic problems under heavy-tailed noise
@inproceedings{bashirov2026zeroth,
title = {Zeroth-order methods for non-smooth stochastic problems under heavy-tailed noise},
author = {Nail Bashirov and Alexander Gasnikov and Aleksandr Lobanov},
booktitle = {Optimization Methods and Software},
year = {2026},
doi = {10.1080/10556788.2026.2617623}
}
We study the problem of identifying edges in a transportation graph where the introduction of an additional toll would enhance the efficiency of network usage within the Nesterov–de Palma equilibrium model.
Identification of the Braess paradox in a stable dynamic model in network with one source and multiple sinks
@inproceedings{shitikov2026brayess,
title = {Identification of the Braess paradox in a stable dynamic model in network with one source and multiple sinks},
author = {Oleg Shitikov and Yuriy Dorn},
booktitle = {Journal of Mathematical Sciences},
year = {2026},
doi = {10.1007/s10958-025-08162-9}
}
A two-path architecture for query-optimizer hint selection that combines fast nearest-neighbor transfer in an LLM-derived plan-embedding space with a budgeted LLM agent that searches the hint space under DBMS feedback.
Hint Based Query Optimization with LLM Agent and Plan Similarity
@inproceedings{vasilenko2025hintqo,
title = {Hint Based Query Optimization with LLM Agent and Plan Similarity},
author = {Nikita Vasilenko and Alexander Demin and Vladimir Burlakov},
booktitle = {APEIE 2025},
year = {2025},
doi = {10.1109/APEIE66761.2025.11289347}
}
UCB-type Algorithm for Budget-Constrained Expert Learning
@inproceedings{latypov2025ucb,
title = {UCB-type Algorithm for Budget-Constrained Expert Learning},
author = {Ilgam Latypov and Alexandra Suvorikova and Alexey Kroshnin and Alexander Gasnikov and Yuriy Dorn},
booktitle = {arXiv},
year = {2025},
url = {https://arxiv.org/abs/2510.22654}
}
Autobidding Arena: unified evaluation of the classical and RL-based autobidding algorithms
@inproceedings{pudovikov2025autobidding,
title = {Autobidding Arena: unified evaluation of the classical and RL-based autobidding algorithms},
author = {Andrey Pudovikov and Aleksandra Khirianova and Ekaterina Solodneva and Aleksandr Katrutsa and Egor Samosvat and Yuriy Dorn},
booktitle = {arXiv},
year = {2025},
url = {https://arxiv.org/abs/2510.19357}
}
RARe: Raising Ad Revenue Framework with Context-Aware Reranking
@inproceedings{solodneva2025rare,
title = {RARe: Raising Ad Revenue Framework with Context-Aware Reranking},
author = {Ekaterina Solodneva and Aleksandra Khirianova and Aleksandr Katrutsa and Roman Loginov and Andrey Tikhanov and Egor Samosvat and Yuriy Dorn},
booktitle = {AAMAS 2026},
year = {2025},
url = {https://arxiv.org/abs/2510.08788}
}
We propose a new method for constructing UCB-type algorithms for stochastic multi-armed bandits based on general convex optimization methods with an inexact oracle.
Fast UCB-type algorithms for stochastic bandits with heavy and super heavy symmetric noise
@inproceedings{dorn2025fast,
title = {Fast UCB-type algorithms for stochastic bandits with heavy and super heavy symmetric noise},
author = {Yuriy Dorn and Aleksandr Katrutsa and Ilgam Latypov and Andrey Pudovikov},
booktitle = {AAMAS 2025},
year = {2025},
url = {https://arxiv.org/abs/2402.07062}
}
An open benchmark and dataset for real-time ad-auction bidding, with baselines for budget pacing and cost-per-click constraints, so autobidding algorithms can be developed and compared on common ground.
@inproceedings{khirianova2025bat,
title = {Bat: Benchmark for auto-bidding task},
author = {Aleksandra Khirianova and Ekaterina Solodneva and Andrey Pudovikov and Sergey Osokin and Egor Samosvat and Yuriy Dorn and Alexander Ledovsky and Yana Zenkova},
booktitle = {Proceedings of the ACM on Web Conference 2025},
year = {2025},
doi = {10.1145/3696410.3714657},
url = {https://arxiv.org/abs/2505.08485}
}
Optimizing Online Advertising with Multi-Armed Bandits: Mitigating the Cold Start Problem under Auction Dynamics
@inproceedings{soboleva2025advertising,
title = {Optimizing Online Advertising with Multi-Armed Bandits: Mitigating the Cold Start Problem under Auction Dynamics},
author = {Anastasiia Soboleva and Andrey Pudovikov and Roman Snetkov and Alina Babenko and Egor Samosvat and Yuriy Dorn},
booktitle = {arXiv},
year = {2025},
url = {https://arxiv.org/abs/2502.01867}
}
Optimal Traffic Allocation for Multi-Slot Sponsored Search: Balance of Efficiency and Fairness
@inproceedings{soboleva2025opt,
title = {Optimal Traffic Allocation for Multi-Slot Sponsored Search: Balance of Efficiency and Fairness},
author = {Anastasiia Soboleva and Alexander Ledovsky and Yuriy Dorn and Egor Samosvat and Andrey Tikhanov and Fyodor Prazdnikov},
booktitle = {arXiv},
year = {2025},
url = {https://arxiv.org/abs/2502.01862}
}
Power of Generalized Smoothness in Stochastic Convex Optimization: First- and Zero-Order Algorithms
@inproceedings{lobanov2025power,
title = {Power of Generalized Smoothness in Stochastic Convex Optimization: First- and Zero-Order Algorithms},
author = {Aleksandr Lobanov and Alexander Gasnikov},
booktitle = {arXiv},
year = {2025},
url = {https://arxiv.org/abs/2501.18198}
}
We introduce an extension of the concept of competitive solutions and propose the Scalarization With Competitiveness Method (SWCM) for multi-criteria problems.
γ-Competitiveness: An Approach to Multi-Objective Optimization with High Computation Costs in Lipschitz Functions
@inproceedings{latypov2025gamma,
title = {γ-Competitiveness: An Approach to Multi-Objective Optimization with High Computation Costs in Lipschitz Functions},
author = {Ilgam Latypov and Yuriy Dorn},
booktitle = {Operations Research Forum},
year = {2025},
url = {https://arxiv.org/abs/2410.03023}
}
On quasi-convex smooth optimization problems by a comparison oracle
@inproceedings{gasnikov2024quasi,
title = {On quasi-convex smooth optimization problems by a comparison oracle},
author = {Alexander Gasnikov and Mohammad Alkousa and Aleksandr Lobanov and Yuriy Dorn and Fedor Stonyakin and Ilya Kuruzov and Sanjeev Singh},
booktitle = {Russian Journal of Nonlinear Dynamics},
year = {2024},
url = {https://arxiv.org/abs/2502.01862}
}
Learning-Augmented Online Caching: New Upper Bounds
@inproceedings{skachkov2024online,
title = {Learning-Augmented Online Caching: New Upper Bounds},
author = {Daniel Skachkov and Denis Ponomaryov and Yuriy Dorn and Alexander Demin},
booktitle = {arXiv},
year = {2024},
url = {https://arxiv.org/abs/2410.01760}
}
EEvA: Fast Expert-Based Algorithms for Buffer Page Replacement
@inproceedings{demin2024eeva,
title = {EEvA: Fast Expert-Based Algorithms for Buffer Page Replacement},
author = {Alexander Demin and Yuriy Dorn and Aleksandr Katrutsa and Daniil Kazantsev and Ilgam Latypov and Yulia Maximlyuk and Denis Ponomaryov},
booktitle = {arXiv},
year = {2024},
url = {https://arxiv.org/abs/2405.00154}
}
Implicitly normalized forecaster with clipping for linear and non-linear heavy-tailed multi-armed bandits
@inproceedings{dorn2024forecaster,
title = {Implicitly normalized forecaster with clipping for linear and non-linear heavy-tailed multi-armed bandits},
author = {Yuriy Dorn and Nikita Kornilov and Nikolay Kutuzov and Alexander Nazin and Eduard Gorbunov and Alexander Gasnikov},
booktitle = {Computational Management Science},
year = {2024},
url = {https://arxiv.org/abs/2305.06743}
}
