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ORCIDYury Maximov
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2020 – today
- 2025
[j11]Massih-Reza Amini, Vasilii Feofanov, Loïc Pauletto, Lies Hadjadj, Emilie Devijver, Yury Maximov:
Self-training: A survey. Neurocomputing 616: 128904 (2025)- 2024
- [j10]Valeriy Shevchenko
, Aleksandr Lukashevich, Daria Taniushkina, Alexander Bulkin, Roland Grinis, Kirill Kovalev, Veronika Narozhnaia, Nazar Sotiriadi, Alexander Krenke, Yury Maximov:
Climate Change Impact on Agricultural Land Suitability: An Interpretable Machine Learning-Based Eurasia Case Study. IEEE Access 12: 15748-15763 (2024) - [j9]Aleksandr Lukashevich, Aleksandr Bulkin, Yury Maximov:
A-Priori Reduction of Scenario Approximation for Automated Generation Control in High-Voltage Power Grids With Renewable Energy. IEEE Control. Syst. Lett. 8: 1613-1618 (2024) - [j8]Alexander Marusov, Vsevolod Grabar, Yury Maximov, Nazar Sotiriadi, Alexander Bulkin, Alexey Zaytsev:
Long-term drought prediction using deep neural networks based on geospatial weather data. Environ. Model. Softw. 179: 106127 (2024) - [j7]Aleksander Lukashevich, Vyacheslav Gorchakov, Petr Vorobev, Deepjyoti Deka, Yury Maximov:
Importance Sampling Approach to Chance-Constrained DC Optimal Power Flow. IEEE Trans. Control. Netw. Syst. 11(2): 928-937 (2024) - [c11]Danil Kononykhin, Mikhail Mozikov, Kirill Mishtal, Pavel Kuznetsov, Dmitrii Abramov, Nazar Sotiriadi, Yury Maximov, Andrey V. Savchenko, Ilya Makarov:
From Data to Decisions: Streamlining Geospatial Operations with Multimodal GlobeFlowGPT. SIGSPATIAL/GIS 2024: 649-652 - [i27]Joe Gorka, Tim Hsu, Wenting Li, Yury Maximov, Line Roald:
Cascading Blackout Severity Prediction with Statistically-Augmented Graph Neural Networks. CoRR abs/2403.15363 (2024) - 2023
- [j6]Mile Mitrovic, Ognjen Kundacina, Aleksandr Lukashevich, Semen A. Budennyy, Petr Vorobev, Vladimir V. Terzija, Yury Maximov, Deepjyoti Deka:
GP CC-OPF: Gaussian Process based optimization tool for Chance-Constrained Optimal Power Flow. Softw. Impacts 16: 100489 (2023) - [c10]Mikhail Mozikov, Ivan Lukyanenko, Ilya Makarov, Alexander Bulkin, Yury Maximov:
Long-Term Hail Risk Assessment with Deep Neural Networks. IWANN (1) 2023: 288-301 - [i26]Mile Mitrovic, Ognjen Kundacina, Aleksandr Lukashevich, Petr Vorobev, Vladimir V. Terzija, Yury Maximov, Deepjyoti Deka:
GP CC-OPF: Gaussian Process based optimization tool for Chance-Constrained Optimal Power Flow. CoRR abs/2302.08454 (2023) - [i25]Vsevolod Grabar, Alexander Marusov, Yury Maximov, Nazar Sotiriadi, Alexander Bulkin, Alexey Zaytsev:
Long-term drought prediction using deep neural networks based on geospatial weather data. CoRR abs/2309.06212 (2023) - [i24]Valeriy Shevchenko, Daria Taniushkina, Aleksandr Lukashevich, Aleksander Bulkin, Roland Grinis, Kirill Kovalev, Veronika Narozhnaia, Nazar Sotiriadi, Alexander Krenke, Yury Maximov:
Climate Change Impact on Agricultural Land Suitability: An Interpretable Machine Learning-Based Eurasia Case Study. CoRR abs/2310.15912 (2023) - [i23]Vsevolod Morozov, Artem Galliamov, Aleksandr Lukashevich, Antonina Kurdukova, Yury Maximov:
CMIP X-MOS: Improving Climate Models with Extreme Model Output Statistics. CoRR abs/2311.03370 (2023) - 2022
- [j5]Aleksandr Lukashevich, Yury Maximov:
Power Grid Reliability Estimation via Adaptive Importance Sampling. IEEE Control. Syst. Lett. 6: 1010-1015 (2022) - [j4]Anton Anikin, Alexander V. Gasnikov, Alexander Gornov, Dmitry Kamzolov, Yury Maximov, Yurii E. Nesterov:
Efficient numerical methods to solve sparse linear equations with application to PageRank. Optim. Methods Softw. 37(3): 907-935 (2022) - [c9]Aleksandra Burashnikova, Marianne Clausel, Massih-Reza Amini, Yury Maximov, Nicolas Dante:
Recommender Systems: When Memory Matters. ECIR (2) 2022: 56-63 - [i22]Massih-Reza Amini, Vasilii Feofanov, Loïc Pauletto, Emilie Devijver, Yury Maximov:
Self-Training: A Survey. CoRR abs/2202.12040 (2022) - [i21]Aleksandra Burashnikova, Yury Maximov, Marianne Clausel, Charlotte Laclau, Franck Iutzeler, Massih-Reza Amini:
Learning over No-Preferred and Preferred Sequence of Items for Robust Recommendation (Extended Abstract). CoRR abs/2202.13240 (2022) - [i20]Mile Mitrovic, Aleksandr Lukashevich, Petr Vorobev, Vladimir V. Terzija, Semen Budenny, Yury Maximov, Deepjyoti Deka:
Data-Driven Stochastic AC-OPF using Gaussian Processes. CoRR abs/2207.10781 (2022) - [i19]Mile Mitrovic, Aleksandr Lukashevich, Petr Vorobev, Vladimir V. Terzija, Yury Maximov, Deepjyoti Deka:
Data-Driven Chance Constrained AC-OPF using Hybrid Sparse Gaussian Processes. CoRR abs/2208.14814 (2022) - [i18]Vsevolod Grabar, Yury Maximov, Alexey Zaytsev:
Predicting spatial distribution of Palmer Drought Severity Index. CoRR abs/2208.14833 (2022) - [i17]Aleksandra Burashnikova, Wenting Li, Massih Amini, Deepjyoti Deka, Yury Maximov:
Ranking-Based Physics-Informed Line Failure Detection in Power Grids. CoRR abs/2209.01021 (2022) - [i16]Ivan Lukyanenko, Mikhail Mozikov, Yury Maximov, Ilya Makarov:
Long-term hail risk assessment with deep neural networks. CoRR abs/2209.01191 (2022) - 2021
- [j3]Sumit Sidana, Mikhail Trofimov, Oleh Horodnytskyi, Charlotte Laclau, Yury Maximov, Massih-Reza Amini:
User preference and embedding learning with implicit feedback for recommender systems. Data Min. Knowl. Discov. 35(2): 568-592 (2021) - [j2]Aleksandra Burashnikova, Yury Maximov, Marianne Clausel, Charlotte Laclau, Franck Iutzeler, Massih-Reza Amini:
Learning over No-Preferred and Preferred Sequence of Items for Robust Recommendation. J. Artif. Intell. Res. 71: 121-142 (2021) - [i15]Aleksandra Burashnikova, Marianne Clausel, Massih-Reza Amini, Yury Maximov, Nicolas Dante:
Recommender systems: when memory matters. CoRR abs/2112.02242 (2021) - 2020
- [i14]Aleksandra Burashnikova, Marianne Clausel, Charlotte Laclau, Frack Iutzeller, Yury Maximov, Massih-Reza Amini:
Learning over no-Preferred and Preferred Sequence of items for Robust Recommendation. CoRR abs/2012.06910 (2020)
2010 – 2019
- 2019
- [c8]Valerii Likhosherstov, Yury Maximov, Misha Chertkov:
Inference and Sampling of $K_33$-free Ising Models. ICML 2019: 3963-3972 - [c7]Mikhail Krechetov, Jakub Marecek, Yury Maximov, Martin Takác:
Entropy-Penalized Semidefinite Programming. IJCAI 2019: 1123-1129 - [c6]Aleksandra Burashnikova, Yury Maximov, Massih-Reza Amini:
Sequential Learning over Implicit Feedback for Robust Large-Scale Recommender Systems. ECML/PKDD (3) 2019: 253-269 - [i13]Nikolay Stulov, Dejan J. Sobajic, Yury Maximov, Deepjyoti Deka, Michael Chertkov:
Learning a Generator Model from Terminal Bus Data. CoRR abs/1901.00781 (2019) - [i12]Alexandra Burashnikova, Yury Maximov, Massih-Reza Amini:
Sequential Learning over Implicit Feedback for Robust Large-Scale Recommender Systems. CoRR abs/1902.08495 (2019) - [i11]Valerii Likhosherstov, Yury Maximov, Michael Chertkov:
A New Family of Tractable Ising Models. CoRR abs/1906.06431 (2019) - [i10]Valerii Likhosherstov, Yury Maximov, Michael Chertkov:
Tractable Minor-free Generalization of Planar Zero-field Ising Models. CoRR abs/1910.11142 (2019) - 2018
- [j1]Yury Maximov, Massih-Reza Amini, Zaïd Harchaoui:
Rademacher Complexity Bounds for a Penalized Multi-class Semi-supervised Algorithm. J. Artif. Intell. Res. 61: 761-786 (2018) - [c5]Andrii Riazanov, Yury Maximov, Michael Chertkov:
Belief Propagation Min-Sum Algorithm for Generalized Min-Cost Network Flow. ACC 2018: 6108-6113 - [c4]Simon Moura, Amir Asarbaev, Massih-Reza Amini, Yury Maximov:
Heterogeneous Dyadic Multi-task Learning with Implicit Feedback. ICONIP (3) 2018: 660-672 - [c3]Yury Maximov, Massih-Reza Amini, Zaïd Harchaoui:
Rademacher Complexity Bounds for a Penalized Multi-class Semi-supervised Algorithm (Extended Abstract). IJCAI 2018: 5637-5641 - [i9]Michael Chertkov, Yury Maximov:
Gauges, Loops, and Polynomials for Partition Functions of Graphical Models. CoRR abs/1811.04713 (2018) - [i8]Valerii Likhosherstov, Yury Maximov, Michael Chertkov:
Inference and Sampling of K33-free Ising Models. CoRR abs/1812.09587 (2018) - 2017
- [c2]Roman Pogodin, Mikhail Krechetov, Yury Maximov:
Efficient rank minimization to tighten semidefinite programming for unconstrained binary quadratic optimization. Allerton 2017: 1153-1159 - [c1]Bikash Joshi, Massih-Reza Amini, Ioannis Partalas, Franck Iutzeler, Yury Maximov:
Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text Classification. NIPS 2017: 4159-4168 - [i7]Bikash Joshi, Massih-Reza Amini, Ioannis Partalas, Franck Iutzeler, Yury Maximov:
Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text Classification. CoRR abs/1701.06511 (2017) - [i6]Mikhail Trofimov, Sumit Sidana, Oleh Horodnitskii, Charlotte Laclau, Yury Maximov, Massih-Reza Amini:
Representation Learning and Pairwise Ranking for Implicit and Explicit Feedback in Recommendation Systems. CoRR abs/1705.00105 (2017) - [i5]Roman Pogodin, Mikhail Krechetov, Yury Maximov:
Efficient Rank Minimization to Tighten Semidefinite Programming for Unconstrained Binary Quadratic Optimization. CoRR abs/1708.01690 (2017) - [i4]Art B. Owen, Yury Maximov, Michael Chertkov:
Importance sampling the union of rare events with an application to power systems analysis. CoRR abs/1710.06965 (2017) - [i3]Andrii Riazanov, Yury Maximov, Michael Chertkov:
Belief Propagation Min-Sum Algorithm for Generalized Min-Cost Network Flow. CoRR abs/1710.07600 (2017) - 2016
- [i2]Yury Maximov, Massih-Reza Amini, Zaïd Harchaoui:
Rademacher Complexity Bounds for a Penalized Multiclass Semi-Supervised Algorithm. CoRR abs/1607.00567 (2016) - 2015
- [i1]Yury Maximov, Daria Reshetova:
Tight Risk Bounds for Multi-Class Margin Classifiers. CoRR abs/1507.03040 (2015)
Coauthor Index
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