Danilova Marina Yuryevna
PhD in Computer Science
Education
2016 — BSc degree in Applied Math and Physics, Moscow Institue of Physics and Technology
2018 — MSc degree in Applied Math and Physics, Moscow Institue of Physics and Technology
2018 — MSc degree in Information Technology and Engineering, Skolkovo Institute of Science and Technology
2022 — PhD in Computer science, Institute for Control Science
Research Interests
Convex optimization, first-order methods, huge-scale optimization, stochastic optimization, combinatorial optimization
Публикации
2024
Gorbunov, E., Danilova, M., Shibaev, I., Dvurechensky, P., Gasnikov, A. High-Probability Complexity Bounds for Non-smooth Stochastic Convex Optimization with Heavy-Tailed Noise (2024) Journal of Optimization Theory and Applications, 203 (3), pp. 2679-2738. Scopus DOI Q1
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Eduard Gorbunov, Abdurakhmon Sadiev, Marina Danilova, Samuel Horváth, Gauthier Gidel, Pavel Dvurechensky, Alexander Gasnikov, Peter Richtárik. High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise (2024) Scopus DOI
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2023
Sadiev, A., Danilova, M., Gorbunov, E., Horváth, S., Gidel, G., Dvurechensky, P., Gasnikov, A., Richtárik, P. High-Probability Bounds for Stochastic Optimization and Variational Inequalities: the Case of Unbounded Variance (2023) Proceedings of Machine Learning Research, 202, pp. 29563-29648. Scopus DOI A*
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2022
Danilova M., Dvurechensky P., Gasnikov A., Gorbunov E., Guminov S., Kamzolov D., Shibaev I. Recent Theoretical Advances in Non-Convex Optimization // Springer Optimization and Its Applications, Vol. 191, P. 79 - 163 Scopus WOS DOI Q3
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2020
Gorbunov, E., Danilova, M., Gasnikov, A. Stochastic optimization with heavy-tailed noise via accelerated gradient clipping (2020) Advances in Neural Information Processing Systems, 2020-December. Scopus WOS DOI A*
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