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Spokoiny, Vladimir Grigor'evich
Statistics Math-Net.Ru
Total publications: 14
Scientific articles: 14
Presentations: 58

Number of views:
This page:5351
Abstract pages:5869
Full texts:2346
References:664
Doctor of physico-mathematical sciences
E-mail:

https://www.mathnet.ru/eng/person21752
List of publications on Google Scholar
List of publications on ZentralBlatt
https://mathscinet.ams.org/mathscinet/MRAuthorID/200375

Publications in Math-Net.Ru Citations
2016
1. A. L. Suvorikova, V. G. Spokoiny, “Multiscale approach for change point detection”, Teor. Veroyatnost. i Primenen., 61:4 (2016),  774–804  mathnet  mathscinet  zmath  elib; Theory Probab. Appl., 61:4 (2017), 665–691  isi  scopus 1
2015
2. A. V. Gasnikov, Yu. E. Nesterov, V. G. Spokoiny, “On the efficiency of a randomized mirror descent algorithm in online optimization problems”, Zh. Vychisl. Mat. Mat. Fiz., 55:4 (2015),  582–598  mathnet  mathscinet  zmath  elib; Comput. Math. Math. Phys., 55:4 (2015), 580–596  isi  elib  scopus 16
2014
3. Maxim E. Panov, Vladimir G. Spokoiny, “Critical dimension in the semiparametric Bernstein–von Mises theorem”, Trudy Mat. Inst. Steklova, 287 (2014),  242–266  mathnet  elib; Proc. Steklov Inst. Math., 287:1 (2014), 232–255  isi  elib  scopus 1
2013
4. M. M. Zhilova, V. G. Spokoiny, “Uniform properties of the local maximum likelihood estimate”, Avtomat. i Telemekh., 2013, no. 10,  68–85  mathnet; Autom. Remote Control, 74:10 (2013), 1656–1669  isi  scopus
5. A. A. Zaytsev, E. V. Burnaev, V. G. Spokoiny, “Properties of the posterior distribution of a regression model based on Gaussian random fields”, Avtomat. i Telemekh., 2013, no. 10,  55–67  mathnet; Autom. Remote Control, 74:10 (2013), 1645–1655  isi  scopus 14
6. A. A. Zaytsev, E. V. Burnaev, V. G. Spokoiny, “Properties of the Bayesian parameter estimation of a regression based on Gaussian processes”, Fundam. Prikl. Mat., 18:2 (2013),  53–65  mathnet  mathscinet; J. Math. Sci., 203:6 (2014), 789–798  scopus 6
7. N. P. Baldin, V. G. Spokoiny, “Bayesian model selection and the concentration of the posterior of hyperparameters”, Fundam. Prikl. Mat., 18:2 (2013),  13–34  mathnet  mathscinet; J. Math. Sci., 203:6 (2014), 761–776  scopus
8. E. V. Burnaev, A. A. Zaytsev, V. G. Spokoiny, “The Bernstein–von Mises theorem for regression based on Gaussian Processes”, Uspekhi Mat. Nauk, 68:5(413) (2013),  179–180  mathnet  mathscinet  zmath  elib; Russian Math. Surveys, 68:5 (2013), 954–956  isi  elib  scopus 12
9. D. V. Belomestny, V. G. Spokoiny, “Concentration inequalities for smooth random fields”, Teor. Veroyatnost. i Primenen., 58:2 (2013),  401–410  mathnet  mathscinet  zmath  elib; Theory Probab. Appl., 58:2 (2014), 314–323  isi  elib  scopus
2007
10. Ion Grama, Vladimir Spokoiny, “Pareto approximation of the tail by local exponential modeling”, Bul. Acad. Ştiinţe Repub. Mold. Mat., 2007, no. 1,  3–24  mathnet  mathscinet  zmath 3
1993
11. V. G. Spokoiny, A. N. Shiryaev, “On the concept of $\lambda$-convergence of statistical experiments”, Trudy Mat. Inst. Steklov., 202 (1993),  282–286  mathnet  mathscinet  zmath; Proc. Steklov Inst. Math., 202 (1994), 225–228
12. V. G. Spokoiny, “On construction of optimal strategies of parameter estimation for controllable systems”, Trudy Mat. Inst. Steklov., 202 (1993),  258–281  mathnet  mathscinet  zmath; Proc. Steklov Inst. Math., 202 (1994), 207–224
13. M. B. Malyutov, L. A. Orna Uaraka, V. G. Spokoiny, “On asymptotic properties of estimates under sequential design”, Trudy Mat. Inst. Steklov., 202 (1993),  190–208  mathnet  mathscinet  zmath; Proc. Steklov Inst. Math., 202 (1994), 155–168
1988
14. V. G. Spokoiny, “On the design of regression experiments with dependent errors”, Uspekhi Mat. Nauk, 43:1(259) (1988),  209–210  mathnet  mathscinet  zmath; Russian Math. Surveys, 43:1 (1988), 255–256  isi 1

Presentations in Math-Net.Ru
1. Linearly Perturbed Optimization with Applications to Machine Learning. Lecture 2
Vladimir Spokoiny
AI Autumn School on Computational Optimization (ASCOMP 2024)
October 8, 2024 15:00
2. Linearly Perturbed Optimization with Applications to Machine Learning. Lecture 1
Vladimir Spokoiny
AI Autumn School on Computational Optimization (ASCOMP 2024)
October 7, 2024 15:00   
3. Worksop on Optimization and applications
P. Richtarik, V. G. Spokoiny, E. E. Tyrtyshnikov, A. V. Nazin, P. E. Dvurechenskii, A. A. Tremba
Mathematical Workshop of the School of Applied Mathematics and Computer Science (MIPT)
September 27, 2019 14:00
4. Large ball probability with applications in statistics
V. G. Spokoiny
Mathematical Workshop of the School of Applied Mathematics and Computer Science (MIPT)
November 30, 2018 18:30
5. Statistical inference with optimal transport
V. G. Spokoiny

April 14, 2018 11:00   
6. Современные методы математической статистики на примере задачи оценки ковариационной матрицы спектральных проекторов
V. G. Spokoiny
Mathematical Workshop of the School of Applied Mathematics and Computer Science (MIPT)
February 16, 2018 18:30   
7. Advanced statistical methods, Lecture 3
V. G. Spokoiny

March 21, 2017   
8. Advanced statistical methods, Lecture 2
V. G. Spokoiny

February 14, 2017   
9. Advanced statistical methods, Lecture 1
V. G. Spokoiny

February 7, 2017   
10. Dimension reduction
V. G. Spokoiny
Problems in Stochastic Analysis
September 10, 2016 11:00   
11. Inference for Structural Nonparametrics. Lecture 6
V. G. Spokoiny
V. G. Spokoinyi, Inference for Structural Nonparametrics
March 1, 2016   
12. Inference for Structural Nonparametrics. Lecture 5
V. G. Spokoiny
V. G. Spokoinyi, Inference for Structural Nonparametrics
February 29, 2016   
13. Inference for Structural Nonparametrics. Lecture 4
V. G. Spokoiny
V. G. Spokoinyi, Inference for Structural Nonparametrics
February 22, 2016   
14. Inference for Structural Nonparametrics. Lecture 3
V. G. Spokoiny
V. G. Spokoinyi, Inference for Structural Nonparametrics
February 17, 2016   
15. Inference for Structural Nonparametrics. Lecture 2
V. G. Spokoiny
V. G. Spokoinyi, Inference for Structural Nonparametrics
February 16, 2016   
16. Inference for Structural Nonparametrics. Lecture 1
V. G. Spokoiny
V. G. Spokoinyi, Inference for Structural Nonparametrics
February 15, 2016   
17. Mini-course "Model Selection". Lecture 6
V. G. Spokoiny
Problems in Stochastic Analysis
March 3, 2015 19:20   
18. Mini-course "Model Selection". Lecture 5
V. G. Spokoiny
Problems in Stochastic Analysis
March 2, 2015 19:20   
19. Mini-course "Model Selection". Lecture 4
V. G. Spokoiny
Problems in Stochastic Analysis
February 24, 2015 19:20   
20. Mini-course "Model Selection". Lecture 3
V. G. Spokoiny
Problems in Stochastic Analysis
February 23, 2015 19:20   
21. Gaussian multiplier bootstrap in high dimension with applications to model selection
V. G. Spokoiny
Colloquium of the Faculty of Computer Science
February 19, 2015 16:40   
22. Multiscale change-point detection
V. G. Spokoiny
PreMoLab Seminar
February 18, 2015 17:00   
23. Mini-course "Model Selection". Lecture 2
V. G. Spokoiny
Problems in Stochastic Analysis
February 17, 2015 19:20   
24. Mini-course "Model Selection". Lecture 1
V. G. Spokoiny
Problems in Stochastic Analysis
February 16, 2015 19:20   
25. From lambda-convergence to Fisher and Wilks expansions
V. G. Spokoiny
Conference "Stochastics, Statistics, Financial Mathematics" in honor of Professor Albert Shiryaev's 80th anniversary
October 13, 2014 14:30   
26. Construction of the sharp confidence bands using multiplier bootstrap
V. G. Spokoiny
Advances in Stochastic Analysis
September 5, 2014 17:00   
27. Modern Parametric Statistics. Lecture 6
V. G. Spokoiny
Problems in Stochastic Analysis
February 25, 2014 19:00   
28. Modern Parametric Statistics. Lecture 5
V. G. Spokoiny
Problems in Stochastic Analysis
February 24, 2014 19:00   
29. Modern Parametric Statistics. Lecture 4
V. G. Spokoiny
Problems in Stochastic Analysis
February 18, 2014 19:00   
30. Modern Parametric Statistics. Lecture 3
V. G. Spokoiny
Problems in Stochastic Analysis
February 17, 2014 19:00   
31. Modern Parametric Statistics. Lecture 2
V. G. Spokoiny
Problems in Stochastic Analysis
February 11, 2014 19:00   
32. Modern Parametric Statistics. Лекция 1
V. G. Spokoiny
V. Spokoinyi course «Modern Parametric Statistics»
February 11, 2014   
33. Modern Parametric Statistics. Lecture 1
V. G. Spokoiny
Problems in Stochastic Analysis
February 10, 2014 19:00   
34. Some topics in predictive modeling
V. G. Spokoiny
PreMoLab Seminar
December 26, 2013 15:30   
35. Задачи современной статистики
V. G. Spokoiny
Mathematical Seminar
November 5, 2013 18:00   
36. Robust clustering using adaptive weights
V. G. Spokoiny
International Workshop on Statistical Learning
June 27, 2013 12:00   
37. Основы современной параметрической статистики. Лекция 6
V. G. Spokoiny
Problems in Stochastic Analysis
February 26, 2013   
38. Основы современной параметрической статистики. Лекция 6
V. G. Spokoiny
V. Spokoinyi course «Modern Parametric Statistics»
February 26, 2013   
39. Основы современной параметрической статистики. Лекция 5
V. G. Spokoiny
Problems in Stochastic Analysis
February 25, 2013   
40. Основы современной параметрической статистики. Лекция 5
V. G. Spokoiny
V. Spokoinyi course «Modern Parametric Statistics»
February 25, 2013   
41. Основы современной параметрической статистики. Лекция 4
V. G. Spokoiny
Problems in Stochastic Analysis
February 19, 2013   
42. Основы современной параметрической статистики. Лекция 4
V. G. Spokoiny
V. Spokoinyi course «Modern Parametric Statistics»
February 19, 2013   
43. Основы современной параметрической статистики. Лекция 3
V. G. Spokoiny
Problems in Stochastic Analysis
February 18, 2013   
44. Основы современной параметрической статистики. Лекция 3
V. G. Spokoiny
V. Spokoinyi course «Modern Parametric Statistics»
February 18, 2013   
45. Основы современной параметрической статистики. Лекция 2
V. G. Spokoiny
Problems in Stochastic Analysis
February 12, 2013   
46. Основы современной параметрической статистики. Лекция 2
V. G. Spokoiny
V. Spokoinyi course «Modern Parametric Statistics»
February 12, 2013   
47. Основы современной параметрической статистики. Лекция 1
V. G. Spokoiny
Problems in Stochastic Analysis
February 11, 2013   
48. Основы современной параметрической статистики. Лекция 1
V. G. Spokoiny
V. Spokoinyi course «Modern Parametric Statistics»
February 11, 2013   
49. Parametric statistics: modern view. Premoday, December, 2013
V. G. Spokoiny
Problems in Stochastic Analysis
December 22, 2012   
50. Пленарное заседание факультета управления и прикладной математики МФТИ (ГУ) на 55-й научной конференции МФТИ. Снижение размерности методом негауссовских компонент
V. G. Spokoiny
Mathematical Seminar
November 24, 2012   
51. Bernstein - von Mises Theorem for quasi-posterior
Spokoiny V.
PreMoLab Seminar
March 16, 2012 17:00
52. Современная параметрическая статистика. Лекция 6
V. G. Spokoiny
Mathematical Seminar
February 28, 2012   
53. Современная параметрическая статистика. Лекция 5
V. G. Spokoiny
Mathematical Seminar
February 27, 2012   
54. Semiparametric alternation: convergence and efficiency
V. G. Spokoiny
Principle Seminar of the Department of Probability Theory, Moscow State University
February 22, 2012 16:45
55. Современная параметрическая статистика. Лекция 4
V. G. Spokoiny
Mathematical Seminar
February 21, 2012   
56. Современная параметрическая статистика. Лекция 3
V. G. Spokoiny
Mathematical Seminar
February 20, 2012   
57. Современная параметрическая статистика. Лекция 2
V. G. Spokoiny
Mathematical Seminar
February 14, 2012   
58. Современная параметрическая статистика. Лекция 1
V. G. Spokoiny
Mathematical Seminar
February 13, 2012   

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