Yury Maximov

According to our database, Yury Maximov authored at least 39 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Cascading Blackout Severity Prediction with Statistically-Augmented Graph Neural Networks.

Joe Gorka, Tim Hsu, Wenting Li, Yury Maximov, Line Roald

CoRR, 2024

Climate Change Impact on Agricultural Land Suitability: An Interpretable Machine Learning-Based Eurasia Case Study.

Valeriy Shevchenko, Aleksandr Lukashevich, Daria Taniushkina, Alexander Bulkin, Roland Grinis, Kirill Kovalev, Veronika Narozhnaia, Nazar Sotiriadi, Alexander Krenke, Yury Maximov

IEEE Access, 2024

2023

GP CC-OPF: Gaussian Process based optimization tool for Chance-Constrained Optimal Power Flow.

Mile Mitrovic, Ognjen Kundacina, Aleksandr Lukashevich, Semen A. Budennyy, Petr Vorobev, Vladimir V. Terzija, Yury Maximov, Deepjyoti Deka

Softw. Impacts, May, 2023

CMIP X-MOS: Improving Climate Models with Extreme Model Output Statistics.

Vsevolod Morozov, Artem Galliamov, Aleksandr Lukashevich, Antonina Kurdukova, Yury Maximov

CoRR, 2023

Climate Change Impact on Agricultural Land Suitability: An Interpretable Machine Learning-Based Eurasia Case Study.

Valeriy Shevchenko, Daria Taniushkina, Aleksandr Lukashevich, Aleksander Bulkin, Roland Grinis, Kirill Kovalev, Veronika Narozhnaia, Nazar Sotiriadi, Alexander Krenke, Yury Maximov

CoRR, 2023

Long-term drought prediction using deep neural networks based on geospatial weather data.

Vsevolod Grabar, Alexander Marusov, Yury Maximov, Nazar Sotiriadi, Alexander Bulkin, Alexey Zaytsev

CoRR, 2023

GP CC-OPF: Gaussian Process based optimization tool for Chance-Constrained Optimal Power Flow.

Mile Mitrovic, Ognjen Kundacina, Aleksandr Lukashevich, Petr Vorobev, Vladimir V. Terzija, Yury Maximov, Deepjyoti Deka

CoRR, 2023

Long-Term Hail Risk Assessment with Deep Neural Networks.

Mikhail Mozikov, Ivan Lukyanenko, Ilya Makarov, Alexander Bulkin, Yury Maximov

Proceedings of the Advances in Computational Intelligence, 2023

2022

Efficient numerical methods to solve sparse linear equations with application to PageRank.

Anton Anikin, Alexander V. Gasnikov, Alexander Gornov, Dmitry Kamzolov, Yury Maximov, Yurii E. Nesterov

Optim. Methods Softw., 2022

Power Grid Reliability Estimation via Adaptive Importance Sampling.

Aleksandr Lukashevich, Yury Maximov

IEEE Control. Syst. Lett., 2022

Long-term hail risk assessment with deep neural networks.

Ivan Lukyanenko, Mikhail Mozikov, Yury Maximov, Ilya Makarov

CoRR, 2022

Ranking-Based Physics-Informed Line Failure Detection in Power Grids.

Aleksandra Burashnikova, Wenting Li, Massih Amini, Deepjyoti Deka, Yury Maximov

CoRR, 2022

Predicting spatial distribution of Palmer Drought Severity Index.

Vsevolod Grabar, Yury Maximov, Alexey Zaytsev

CoRR, 2022

Data-Driven Chance Constrained AC-OPF using Hybrid Sparse Gaussian Processes.

Mile Mitrovic, Aleksandr Lukashevich, Petr Vorobev, Vladimir V. Terzija, Yury Maximov, Deepjyoti Deka

CoRR, 2022

Data-Driven Stochastic AC-OPF using Gaussian Processes.

Mile Mitrovic, Aleksandr Lukashevich, Petr Vorobev, Vladimir V. Terzija, Semen Budenny, Yury Maximov, Deepjyoti Deka

CoRR, 2022

Learning over No-Preferred and Preferred Sequence of Items for Robust Recommendation (Extended Abstract).

Aleksandra Burashnikova, Yury Maximov, Marianne Clausel, Charlotte Laclau, Franck Iutzeler, Massih-Reza Amini

CoRR, 2022

Self-Training: A Survey.

Massih-Reza Amini, Vasilii Feofanov, Loïc Pauletto, Emilie Devijver, Yury Maximov

CoRR, 2022

Recommender Systems: When Memory Matters.

Aleksandra Burashnikova, Marianne Clausel, Massih-Reza Amini, Yury Maximov, Nicolas Dante

Proceedings of the Advances in Information Retrieval, 2022

2021

Learning over No-Preferred and Preferred Sequence of Items for Robust Recommendation.

Aleksandra Burashnikova, Yury Maximov, Marianne Clausel, Charlotte Laclau, Franck Iutzeler, Massih-Reza Amini

J. Artif. Intell. Res., 2021

User preference and embedding learning with implicit feedback for recommender systems.

Sumit Sidana, Mikhail Trofimov, Oleh Horodnytskyi, Charlotte Laclau, Yury Maximov, Massih-Reza Amini

Data Min. Knowl. Discov., 2021

2020

Learning over no-Preferred and Preferred Sequence of items for Robust Recommendation.

Aleksandra Burashnikova, Marianne Clausel, Charlotte Laclau, Frack Iutzeller, Yury Maximov, Massih-Reza Amini

CoRR, 2020

2019

Tractable Minor-free Generalization of Planar Zero-field Ising Models.

Valerii Likhosherstov, Yury Maximov, Michael Chertkov

CoRR, 2019

A New Family of Tractable Ising Models.

Valerii Likhosherstov, Yury Maximov, Michael Chertkov

CoRR, 2019

Learning a Generator Model from Terminal Bus Data.

Nikolay Stulov, Dejan J. Sobajic, Yury Maximov, Deepjyoti Deka, Michael Chertkov

CoRR, 2019

Sequential Learning over Implicit Feedback for Robust Large-Scale Recommender Systems.

Aleksandra Burashnikova, Yury Maximov, Massih-Reza Amini

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Entropy-Penalized Semidefinite Programming.

Mikhail Krechetov, Jakub Marecek, Yury Maximov, Martin Takác

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Inference and Sampling of $K_33$-free Ising Models.

Valerii Likhosherstov, Yury Maximov, Misha Chertkov

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Rademacher Complexity Bounds for a Penalized Multi-class Semi-supervised Algorithm.

Yury Maximov, Massih-Reza Amini, Zaïd Harchaoui

J. Artif. Intell. Res., 2018

Inference and Sampling of K₃₃-free Ising Models.

Valerii Likhosherstov, Yury Maximov, Michael Chertkov

CoRR, 2018

Gauges, Loops, and Polynomials for Partition Functions of Graphical Models.

Michael Chertkov, Yury Maximov

CoRR, 2018

Rademacher Complexity Bounds for a Penalized Multi-class Semi-supervised Algorithm (Extended Abstract).

Yury Maximov, Massih-Reza Amini, Zaïd Harchaoui

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Heterogeneous Dyadic Multi-task Learning with Implicit Feedback.

Simon Moura, Amir Asarbaev, Massih-Reza Amini, Yury Maximov

Proceedings of the Neural Information Processing - 25th International Conference, 2018

Belief Propagation Min-Sum Algorithm for Generalized Min-Cost Network Flow.

Andrii Riazanov, Yury Maximov, Michael Chertkov

Proceedings of the 2018 Annual American Control Conference, 2018

2017

Importance sampling the union of rare events with an application to power systems analysis.

Art B. Owen, Yury Maximov, Michael Chertkov

CoRR, 2017

Representation Learning and Pairwise Ranking for Implicit and Explicit Feedback in Recommendation Systems.

Mikhail Trofimov, Sumit Sidana, Oleh Horodnitskii, Charlotte Laclau, Yury Maximov, Massih-Reza Amini

CoRR, 2017

Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text Classification.

Bikash Joshi, Massih-Reza Amini, Ioannis Partalas, Franck Iutzeler, Yury Maximov

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Efficient rank minimization to tighten semidefinite programming for unconstrained binary quadratic optimization.

Roman Pogodin, Mikhail Krechetov, Yury Maximov

Proceedings of the 55th Annual Allerton Conference on Communication, 2017

2016

Rademacher Complexity Bounds for a Penalized Multiclass Semi-Supervised Algorithm.

Yury Maximov, Massih-Reza Amini, Zaïd Harchaoui

CoRR, 2016

2015

Tight Risk Bounds for Multi-Class Margin Classifiers.

Yury Maximov, Daria Reshetova

CoRR, 2015