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Sample space reducing for statistical decision effectiveness increasing
P. 501-506.
Tsitovich F. I., Tsitovich I. I.
We apply the suboptimal sequential nonparametric hypotheses testing approach for effectiveness of a statistical decision by sample space reducing. Numerical examples of the sample space reducing are given when an appropriate reducing makes it possible to construct robust sequential nonparametric hypotheses testing with a smaller mean duration time then one on the total sample space. © 2014 IEEE.
Language:
English
Tsitovich I. I., Tsitovich F. I., International Journal "Information Models and Analyses" 2013 Vol. 2 No. 1 P. 62-69
We study the problem of testing composite hypotheses versus composite alternatives when there is a slight deviation between the model and the real distribution. The used approach, which we called sub-optimal testing, implies an extension of the initial model and a modification of a sequential statistically significant test for the new model. The sub-optimal test ...
Added: July 21, 2013
Tsitovich I. I., , in : Analytical and computational methods in probability theory and its applications (ACMPT-2017). Proceedings of the International Scientific Conference. : M. : RUDN, 2017. P. 509-522.
We study the problem of parameters estimating if there is a slight deviation between the parametric model
and real distributions. The estimator is based on suboptimal testing of builded by a special way
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[б.и.], 2017
Book of abstracts ...
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Panchenko P. N., Право и государство: теория и практика 2011 № 8 С. 104-110
This article analyzes the issues of crime statistics, it`s showing particular use in criminal law and criminology, disclosed reserves replenishment of criminal law, criminology and criminology resource - a resource of criminal law, argues the need for a substantial update as one and the other sciences, formulated conclusions on enhancing their effectiveness in the context ...
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In reliable decision-making systems based on machine learning, models have to be robust to distributional shifts or provide the uncertainty of their predictions. In node-level problems of graph learning, distributional shifts can be especially complex since the samples are interdependent. To evaluate the performance of graph models, it is important to test them on diverse ...
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Anna Melman, Oleg Evsutin, Journal of Visual Communication and Image Representation 2024 Vol. 99 Article 104073
Image watermarking is an effective and promising technology. Robust watermarks, resistant to various attacks, allow authors and owners of digital images to protect their rights to digital content, control its distribution and confirm its authenticity. Most of the modern algorithms for robust image watermarking aim to achieve resistance to a large number of different attacks. ...
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Abdrakhmanova G., Vasilkovsky S., Vishnevskiy K. et al., М. : Национальный исследовательский университет "Высшая школа экономики", 2022
Доклад, подготовленный Институтом статистических исследований и экономи- ки знаний (ИСИЭЗ) Национального исследовательского университета «Высшая школа экономики» (НИУ ВШЭ) по заказу АНО «Координационный центр национального домена сети Интернет» продолжает серию ежегодных публикаций о тенденциях развития интернета. Исследование проводилось по четырем основным направлениям: «анатомия» интернета (доменное пространство, телекоммуникационная инфраструктура, безопасность в сети), интернет для экономики (цифровизация отраслей ...
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Sharipova A., Арьков В. Ю., Вестник Южно-Уральского государственного университета. Серия: Компьютерные технологии, управление, радиоэлектроника 2017 Vol. 17 No. 3 P. 88-98
A practical approach to estimating of the investment strategy robustness is presented. As a quantitative measure of robustness, the objective function smoothness degree is proposed for utilization. After the optimization has been conducted, it is essential to utilize an additional criterion for the selection of strategies that possess better robustness property. The utilization of the ...
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Savchenko A., , in : Proceedings of the IEEE 12th International Symposium on Applied Computational Intelligence and Informatics (SACI 2018). : IEEE, 2018. P. 515-520.
This paper is focused on still-to-video face recog- nition with large number of subjects based on computation of distances between high-dimensional embeddings extracted using deep convolution neural networks. We propose to utilize granular structures and sequentially process granular representations of all frames of the input video. The coarse-grained granules include only low number of the ...
Added: September 17, 2018
[б.и.], 2018
Proceedings of Machine Learning Research. Artificial Intelligence and Statistics, 9-11 April 2018, Playa Blanca, Lanzarote, Canary Islands ...
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Mkhitarian V., Dubrova T. A., Минашкин В. Г. et al., М. : Издательский центр «Академия», 2017
В учебнике рассмотрены функции статистки и её роль в условиях рыночных отношений. Изложены основные понятия статистического исследования и его организации. Приведены формы статистической отчётности; показаны способы проверки отчётных данных, типы ошибок, встречающихся в отчётах, и пути их предупреждения. ...
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Kapuza A., Education Sciences 2020 Vol. 91 No. 10(4) P. 1-13
Concept mapping is a popular tool for knowledge structure assessment. In recent years, both the amount of research about concept maps and their measurement ability have grown. It has been shown that concept maps with different types of tasks, for instance, links between concepts given or selected by a respondent, provide information about the different ...
Added: April 1, 2020
Fursov K., Miles I. D., / Высшая школа экономики. Series WP BRP "Science, Technology and Innovation". 2013. No. 15.
How can we think about the implications of radical technological change for employment and skills? Given the long lead-times required to train professionals, this is an important question, and standard approaches to modeling employment and occupational trends only provide limited parts of the answer. Innovation studies provide us with some further tools for tackling the ...
Added: July 24, 2013
Sherstinova T., Martynenko G., , in : Digital Transformation and Global Society. Fourth International Conference, DTGS 2019, St. Petersburg, Russia, June 19–21, 2019, Revised Selected Papers. : Springer, 2019. P. 719-731.
Digital technologies provide new possibilities for studying cultural heritage. Thus, literature research involving large text corpora allows to set and solve theoretical problems which previously had no prospects for their decision. For example, it has become possible to model the literary system for some defi-nite literary period (i.e., for the Silver Age of Russian literature) ...
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Kroshnin A., Sobolevski A., / Cornell University. Series arXiv "math". 2015. No. 1512.08421.
Endow the space P(R) of probability measures on R with a transportation cost J(mu, nu) generated by a translation-invariant convex cost function. For a probability distribution on P(R) we formulate a notion of average with respect to this transportation cost, called here the Fréchet barycenter, prove a version of the law of large numbers for ...
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Sokolova A., Savchenko A., Optical Memory and Neural Networks (Information Optics) 2020 Vol. 29 No. 1 P. 19-29
The goal of the study is to increase the computation efficiency of the face recognition that uses feature vectors to describe facial images on photos and videos. These high-dimensional feature vectors are nowadays produced by convolutional neural networks. The methods to aggregate the features generated for each video frame are used to process the video ...
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Учебник охватывает все основные разделы курса теории вероятностей и математической статистики. В первой части учебника «Теория вероятностей» изложены основные сведения, относящиеся к изучению случайных событий, случайных величин и законов их распределения, систем случайных величин, законов распределения функций случайных величин, предельных теорем теории вероятностей.
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Added: October 29, 2019
[б.и.], 2017
Proceedings of Machine Learning Research 2017. Vol. Volume 54: Artificial Intelligence and Statistics ...
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PMLR, 2019
Proceedings of Machine Learning Research, Volume 89: The 22nd International Conference on Artificial Intelligence and Statistics, 16-18 April 2019, Naha, Okinawa, Japan ...
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Gokhberg L., Ponomarenko A., Mkhitarian V. et al., Вопросы статистики 2008 № 10 С. 74-80
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