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Photometric data-driven classification of Type Ia supernovae in the open Supernova Catalog
Astronomy and Computing. 2021. Vol. 35. P. 1-10.
We propose a novel approach for a machine-learning-based detection of the type Ia supernovae using photometric information. Unlike other approaches, only real observation data is used during training. Despite being trained on a relatively small sample, the method shows good results on real data from the Open Supernovae Catalog. We also investigate model transfer from the PLAsTiCC simulations train dataset to real data application, and the reverse, and find the performance significantly decreases in both cases, highlighting the existing differences between simulated and real data.
Priority areas:
IT and mathematics
Language:
English
A. Maevskiy, F. Ratnikov, Zinchenko A. et al., The European Physical Journal C - Particles and Fields 2021 Vol. 81 Article 599
High energy physics experiments rely heavily on the detailed detector simulation models in many tasks. Running these detailed models typically requires a notable amount of the computing time available to the experiments. In this work, we demonstrate a new approach to speed up the simulation of the Time Projection Chamber tracker of the MPD experiment at ...
Added: July 12, 2021
V.Belavin, A.Filatov, A.Ustyuzhanin et al., Journal of Physics: Conference Series 2018 Vol. 1085 No. 4 P. 042025-1-042025-6
Traces of electro-magnetic showers in the neutrino experiments may be considered as signals of dark-matter particles. For example, SHiP experiment is going to use emulsion film detectors similar to the ones designed for OPERA experiment from dark matter search. The goal of this research is to develop an algorithm that can identify traces of electro-magnetic ...
Added: December 8, 2017
Ratnikov F., Viktoria Chekalina, Journal of Physics: Conference Series 2018 Vol. 1085 P. 1-5
Reconstruction and identification of particles in calorimeters of modern High Energy Physics experiments is a complicated task. Solutions are usually driven by a priori knowledge about expected properties of reconstructed objects. Such an approach is also used to distinguish single photons in the electromagnetic calorimeter of the LHCb detector at the LHC from overlapping photons ...
Added: October 18, 2018
Chertenkov V., Shchur L., Journal of Physics: Conference Series 2021 Vol. 1740 P. 1-5
We formulate the problem of the universality class investigation using machine learning. We chose an example of the universality class of the two-dimensional 4-state Potts model. There are four known models within the universality class – the 4-state Potts model, the Baxter-Wu model, the Ashkin-Teller model, and the Turban model. All four of them together ...
Added: February 19, 2021
Pruzhinskaya M., Ishida E. O., Novinskaya A. et al., Astronomy and Astrophysics 2023 Vol. 672 Article A111
Context. We provide the first results from the complete SNAD adaptive learning pipeline in the context of a broad scope of data from
large-scale astronomical surveys.
Aims. The main goal of this work is to explore the potential of adaptive learning techniques in application to big data sets.
Methods. Our SNAD team used Active Anomaly Discovery (AAD) as ...
Added: June 6, 2023
Romanov A., Ломотин К. Е., Козлова Е. С., Информационные технологии 2017 Т. 23 № 6 С. 418-423
The paper deals with the applicability of modern machine learning methods to the problem of automatic generation of UDC for scientific articles. As the classifiers, such models as artificial neural networks, logistic regression and boosting are considered. Graph algorithms and a prototype software module to generate UDC are designed. ...
Added: July 30, 2017
Нужный А. С., Однолько И. С., Глухов А. Ю. et al., Прикладная математика и вопросы управления 2021 № 1 С. 7-22
The paper proposes a mathematical model to optimize the operation of the tar hydrocracking unit.
The purpose of modeling is to improve the economic effect of product output by selecting optimal parameters,
such as hydrogen flow rate and reactor temperature. Hot Filtered Precipitation (HFT) is used as a target.
The model involves the search for the minimum value ...
Added: April 11, 2021
Borisyak M., Kazeev N., Journal of Physics: Conference Series 2020 Vol. 1525 Article 012088
Data analysis in high energy physics has to deal with data samples produced from different sources. One of the most widely used ways to unfold their contributions is the sPlot technique. It uses the results of a maximum likelihood fit to assign weights to events. Some weights produced by sPlot are by design negative. Negative ...
Added: October 5, 2021
Emmanuel I. C., Mitrofanova E., / Cornell Tech. Series 4064475 "ArXiv Preprint". 2022.
The paper is devoted to the study of the model fairness and process fairness of the Russian demographic dataset by making predictions of divorce of the 1st marriage, religiosity, 1st employment and completion of education. Our goal was to make classifiers more equitable by reducing their reliance on sensitive features while increasing or at least ...
Added: May 31, 2022
V'yugin V., М. : МЦНМО, 2013
Книга предназначена для первоначлаьного знакомства с математическими основами современной теории машинного обучения (Machine Learning) и теории игр на предсказания. В первой части излагаются основы статистической теории машинного обучения, рассматриваются задачи классификации и регрессии с опорными векторами, теория обобщения и алгоритмы построения разделяющих гиперплоскостей. Во второй и третьей частях рассматриваются задачи адаптивного прогнозирования в нестохастических теоретико-игровой ...
Added: July 9, 2014
Ekaterinburg : CEUR Workshop Proceedings, 2014
AIST'2014 is an international data science conference on Analysis of Images, Social Networks, and Texts. Traditionally, the conference is held annually in Yekaterinburg, Russia. The conference is intended for computer scientists and practitioners whose research interests involve Internet mathematics and other related fields of data science.
LIST OF TOPICS (NON EXHAUSTIVE)
Applications of Data Mining and Machine ...
Added: August 28, 2014
Berlin : Springer, 2014
This book constitutes the proceedings of the Third International Conference on Analysis of Images, Social Networks and Texts, AIST 2014, held in Yekaterinburg, Russia, in April 2014. The 11 full and 10 short papers were carefully reviewed and selected from 74 submissions. They are presented together with 3 short industrial papers, 4 invited papers and ...
Added: November 13, 2014
Хромов С. К., Кулагин М. А., Sidorenko V., Journal of Physics: Conference Series 2020 No. 1680 (1) Article 012019
The article presents the results of the analysis of determining the possibility of Machine Learning (ML) using for solving the problems of incident classification of users on the example of enterprise resource planning (ERP) systems of JSC Russian Railways and choosing a rational method for solving this problem. The presented problem is a special case ...
Added: April 16, 2021
Kuznetsov V. O., Логистика и управление цепями поставок 2018 № 4 (87) С. 27-33
One of the options for a more flexible approach to analyzing the reliability of supply chains is the principal component analysis (PCA). With a large number of variables describing supply chain, it is a difficult task to analyze the structure of variables in two-dimensional space. Within the analysis of the variables dependencies PCA allows to ...
Added: November 29, 2018
Krylova D., Maksimenko A., Государственное управление. Электронный вестник 2021 № 84 С. 241-255
In this article, the authors, using the example of several foreign publications, analyze the trends in the use of artificial intelligence and machine learning in discernment of corruption. Based on the international review, the authors make the conclusion that the mechanisms for detecting corruption, based on the use of artificial intelligence, described in foreign sources, ...
Added: February 25, 2021
IEEE, 2020
Added: October 3, 2020
Chelyabinsk : IEEE, 2018
The 2018 Global Smart Industry Conference is organized in order to exchange experience, promote discussion and presentation of research papers, and summarize results in development of innovative models, methods and technologies for the digital industry in universities, scientific and industrial associations of the Russian Federation as well as in foreign companies, and the experience of ...
Added: November 25, 2019
Izmailov P., Kropotov D., Journal of machine learning and data analysis 2017 Vol. 3 No. 1 P. 20-35
Background: Gaussian processes (GP) provide an elegant and effective approach to learning in kernel machines. This approach leads to a highly interpretable model and allows using the Bayesian framework for model adaptation and incorporating the prior knowledge about the problem. The GP framework is successfully applied to regression, classification, and dimensionality reduction problems. Unfortunately, the ...
Added: December 6, 2018
Braslavski P. undefined., Markov I., Pardalos P. M. et al., ACM SIGIR Forum 2016 Vol. 49 No. 2 P. 72-79
This paper provides the reader with a report on 9th Russian Summer School in Information Retrieval (RuSSIR 2015). ...
Added: February 27, 2017
Рысаков С. В., Системный администратор 2015 № 10(155) С. 92-95
The article provides a review of modern methods of morphological ambiguity resolution. We considered such methods as statistical disambiguation, Brill’s automatically generated rules, decision trees and their modifications. For the comparison, the article provides numerical results obtained on two open corpora: OpenCorpora and SynTagRus. ...
Added: November 25, 2015
Springer, 2021
This book constitutes the proceedings of the 16th International Conference on Formal Concept Analysis, ICFCA 2021, held in Strasbourg, France, in June/July 2021.
The 14 full papers and 5 short papers presented in this volume were carefully reviewed and selected from 32 submissions. The book also contains four invited contributions in full paper length.
The research part ...
Added: July 10, 2021
Polyakov E. V., Мажанов М. С., Качалова М. В. et al., Системный администратор 2017 № 12 С. 80-85
The development of cognitive technologies contributes to the effective introduction of Artificial Intelligence into the everyday life of a person. New interfaces for device-human interaction appear. Understanding the natural language of human is one of the most promising areas of the development of Artificial Intelligence. Voice assistants are a striking example of such systems, they ...
Added: December 10, 2017