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Proceedings 16th International Symposium, ISBRA 2020, Moscow, Russia, December 1–4, 2020. Lecture Notes in Computer Science
Vol. 12304.
Springer Publishing Company, 2020.
Academic editor: Z. Cai, I. Mandoiu, G. Narasimhan, P. Skums, X. Guo
This book constitutes the proceedings of the 16th International Symposium on Bioinformatics Research and Applications, ISBRA 2020, held in Moscow, Russia, in December 2020.
The 23 full papers and 18 short papers presented in this book were carefully reviewed and selected from 131 submissions. They were organized in topical sections named: genome analysis; systems biology; computational proteomics; machine and deep learning; and data analysis and methodology.
Cheloshkina K., Bzhikhatlov I., Poptsova M., , in : Proceedings 16th International Symposium, ISBRA 2020, Moscow, Russia, December 1–4, 2020. Lecture Notes in Computer Science. Vol. 12304.: Springer Publishing Company, 2020. P. 217-228.
Genome rearrangement is a hallmark of all cancers. Cancer breakpoint prediction appeared to be a difficult task, and various machine learning models did not achieve high prediction power. We investigated the power of machine learning models to predict breakpoint hotspots selected with different density thresholds and also compared prediction of hotspots versus individual breakpoints. We ...
Added: November 3, 2020
Springer, 2020
Added: September 8, 2020
Kitov V. V., Экономика, статистика и информатика. Вестник УМО 2016 № 4 С. 22-26
Gradient boosting method with random rotations is considered, where before training each base learner random rotation is applied to the feature space. The accuracy metric of the given method is estimated for a broad range of generated problems of binary classification. Obtained results are evaluated and recommendations given for application of this method. ...
Added: August 23, 2016
Krylov V., Krylov S., Journal of Physics: Conference Series 2018 Т. 1117 № conference 1
Reservoir Computing (RC) is taking attention of neural networks structures developers because of machine learning algorithms are simple at the high level of generalization of the models. The approaches are numerous. RC can be applied to different architectures including recurrent neural networks with irregular connections that are called Echo State Networks (ESN). However, the existence ...
Added: November 15, 2018
Budin E., Smirnova K., Suvorova A. et al., , in : Digital Transformation and Global Society: 4th International Conference, DTGS 2019, St. Petersburg, Russia, June 19–21, 2019, Revised Selected Papers. : Cham : Springer, 2019. P. 461-467.
Information from users’ profiles on social networking sites is an important data source for analysis of the users’ psychological characteristics. Texts, video and audio files, images, public pages can be easily accessible and analyzed. We consider the ways of estimating the users’ psychological characteristics on the base of his or her profile in the social ...
Added: November 27, 2019
Kashnitsky Y., Kuznetsov S., , in : CLA 2016: Proceedings of the Thirteenth International Conference on Concept Lattices and Their Applications. CEUR Workshop Proceedings. Vol. 1624.: M. : Higher School of Economics, National Research University, 2016. Ch. 19. P. 189-202.
Nowadays decision tree learning is one of the most popular classification and regression techniques. Though decision trees are not accurate on their own, they make very good base learners for advanced tree-based methods such as random forests and gradient boosted trees. However, applying ensembles of trees deteriorates interpretability of the final model. Another problem is ...
Added: October 6, 2016
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
Durandin O., Hilal N., Strebkov D. et al., , in : Proceedings of the ISMW-FRUCT 2016. : [б.и.], 2016. P. 90-93.
The paper contains a take on the classification problem variation featuring class noise where each object in the training set is associated with a probability distribution over the class label set instead of a particular class label. That type of task was illustrated on the complex natural language processing problem – automatic Arabic dialect classification. ...
Added: January 17, 2017
Popkov Y., Dubnov Y. A., Volkovich Z. et al., Entropy 2017 Vol. 19(4) No. 178 P. 1-14
A proposal for a new method of classification of objects of various nature, named “2”-soft classification, which allows for referring objects to one of two types with optimal entropy probability for available collection of learning data with consideration of additive errors therein. A decision rule of randomized parameters and probability density function (PDF) is formed, ...
Added: May 26, 2017
Bulychev A., Сомов О. Д., В кн. : Информатика, управление и системный анализ: Труды V Всероссийской научной конференции молодых ученых с международным участием. : Ростов н/Д : Ростовский государственный экономический университет "РИНХ", 2018. С. 94-102.
In the process of developing an information system for logistics transportation, there is a need to determine the initial rating of the new carrier within the parent company. The presence of the rating helps to more accurately carry out the formation of orders and build forecasts of its interaction with the parent company in the ...
Added: September 3, 2019
Kashnitsky Y., Ignatov D. I., Интеллектуальные системы. Теория и приложения 2015 Т. 19 № 4 С. 37-55
The paper makes a brief introduction into multiple classifier systems and describes a particular algorithm which improves classification accuracy by making a recommendation of an algorithm to an object. This recommendation is done under a hypothesis that a classifier is likely to predict the label of the object correctly if it has correctly classified its ...
Added: December 7, 2015
Cham : Springer, 2020
21st International Conference, Guimaraes, Portugal, November 4–6, 2020, Proceedings, Part II
Editors
(view affiliations)
Cesar Analide
Paulo Novais
David Camacho
Hujun Yin
Conference proceedings IDEAL 2020 ...
Added: October 31, 2020
Ignatov D. I., Zhuk R., Konstantinova N., , in : Proceedings of The 2014 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2014, 11-14 August 2014 Warsaw, Poland. : Los Alamitos, Washington, Tokyo : IEEE Computer Society, 2014. P. 474-480.
We propose extensions of the classical JSM-method andtheNa ̈ıveBayesianclassifierforthecaseoftriadicrelational data. We performed a series of experiments on various types of data (both real and synthetic) to estimate quality of classification techniques and compare them with other classification algorithms that generate hypotheses, e.g. ID3 and Random Forest. In addition to classification precision and recall we also ...
Added: June 9, 2014
Zhuk R., Ignatov D. I., Konstantinova N., Procedia Computer Science 2014 Vol. 31 P. 928-938
We propose extensions of the classical JSM-method and the Na ̈ıve Bayesian classifier for the case of triadic relational data. We performed a series of experiments on various types of data (both real and synthetic) to estimate quality of classification techniques and compare them with other classification algorithms that generate hypotheses, e.g. ID3 and Random ...
Added: June 9, 2014
Феста Ю. Ю., Воробьев И. А., Model Assisted Statistics and Applications 2022 Vol. 17 No. 1 P. 41-49
We currently see a large increase in e-commerce sector; it is becoming a central trend in the banking industry. Fraudsters keep up with modern technologies, and use weak points in human psychology and security systems to steal money from regular users. To ensure the required level of security, banks began to apply artificial intelligence in ...
Added: April 13, 2022
Suvorova A., Смирнова К. Р., Будин Е. А. et al., Компьютерные инструменты в образовании 2018 № 3 С. 49-64
The article describes a student research project on predicting the class of a post on a social network based on its textual content. The features of the project are discussed as an integral part of the trajectory of teaching data analysis methods, including text analysis methods and tools that are often not included in machine ...
Added: January 28, 2019
Curran Associates, Inc., 2023
Proceedings of the international conference "Neural Information Processing Systems 2023." (NeurIPS 2023) ...
Added: February 15, 2024
Kashnitsky Y., Kuznetsov S., , in : Proceedings of the International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI at ECAI 2016). : M. : [б.и.], 2016. P. 105-112.
Decision tree learning is one of the most popular classifica- tion techniques. However, by its nature it is a greedy approach to finding a classification hypothesis that optimizes some information-based crite- rion. It is very fast but may lead to finding suboptimal classification hy- potheses. Moreover, in spite of decision trees being easily interpretable, ensembles ...
Added: October 6, 2016
Andrey Okhotin, Dmitry Molchanov, Arkhipkin V. et al., , in : Advances in Neural Information Processing Systems 36 (NeurIPS 2023). : Curran Associates, Inc., 2023. P. 10038-10067.
Added: February 15, 2024
Vlasenko D., Zaikin A., Zakharov D., Известия высших учебных заведений. Прикладная нелинейная динамика 2023 Т. 31 № 5 С. 661-669
Because the brain is an extremely complex hypernet of interacting macroscopic subnetworks, full-scale analysis of brain activity is a daunting task.Nevertheless,this task can be greatly simplified by analysing the correspondence between various patterns of macroscopic brain activity, forex ample,through functional magneticresonance imaging(fMRI) scans, and the performance of particular cognitive tasks or pathological states.The purpose of ...
Added: October 4, 2023
, in : 2017 10th Iranian Conference on Machine Vision and Image Processing (MVIP). : IEEE, 2017. P. 31-38.
In recent years many research works have been devoted either to anomaly detection or anomaly classification. However, very few of them address both of them simultaneously. In this paper, we introduced a new method not only to detect and localize the abnormalities in crowded scenes but also to determine the class of abnormality. In This ...
Added: November 1, 2020
Association for Computing Machinery (ACM), 2020
ASONAM '20: International Conference on Advances in Social Networks Analysis and Mining, 7-10 December 2020, The Hague, Netherlands (Virtual). ...
Added: October 31, 2020
Aksiotis V., Kharitonova A., Видяйкина А. А. et al., В кн. : Материалы Международного молодежного научного форума «ЛОМОНОСОВ-2022». : М. : МАКС Пресс, 2022. С. 1-2.
Numerous modern studies are aimed at creating a tool that is effective in classifying and recognizing emotions and their facial expressions based on electromyography (EMG). Technological developments in the field of virtual reality are underway to optimize human-computer interaction. Based on the results of changes in the electrical activity of the muscles, a judgment is ...
Added: October 26, 2022
Springer, 2019
This 2-volume set constitutes the refereed proceedings of the 9th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2019, held in Madrid, Spain, in July 2019.
The 99 papers in these volumes were carefully reviewed and selected from 137 submissions. They are organized in topical sections named:
Part I: best ranked papers; machine learning; pattern recognition; ...
Added: September 23, 2019