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News
June 4, 2026
Machine Learning Models Can Help Reduce Volatility and Boost Stock Market Returns
The use of machine learning models makes it possible to achieve greater accuracy in predicting risks in the Russian stock market compared to classical econometric approaches. The predictive power of these models increases by 23%, while the average investor’s return can reach up to 13% per annum. These conclusions were drawn by Nikita Lysenok from the Department of Financial Market Infrastructure at the HSE Faculty of Economic Sciences. The paper has been published in Fundamental and Applied Mathematics.
June 3, 2026
Pocket Money, Personal Interest, and Family Practices: What Shapes Students Economic Literacy?
University students' economic literacy depends not only on their field of study but also on their interest in economics, the learning environment, and family financial practices. For example, students who received pocket money irregularly tend to perform better on economic literacy tests than their peers who received financial support on a regular basis. These findings come from a study conducted by HSE University involving more than 1,100 students from five Russian universities. The findings have been published in Cakrawala Pendidikan.
June 3, 2026
Creative Work as a Remedy for Burnout
The creative, supportive atmosphere and innovative methods at the Centre for Sociocultural Research make it appealing to early-career scholars. Over years of working at HSE University, they grow into researchers and lecturers recognised both in Russia and abroad. Chief Research Fellow Zarina Lepshokova and Leading Research Fellow Ekaterina Bushina spoke about their journey at the centre and at HSE, their research, and the role of mentors in their academic success.

 

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CEUR Workshop Proceedings

Vol. 2258: Proceedings of the II International Scientific and Practical Conference “Fuzzy Technologies in the Industry – FTI 2018”. Ulyanovsk : CEUR Workshop Proceedings, 2018.
Editor-in-chief: V. Moshkin, N. Yarushkina, T. Afanasyeva, P. Sosnin

This compilation presents the reports presented at four sectional meetings at the Second International Scientific and Practical Conference Fuzzy Technologies in the Industry - 2018 (FTI 2018). The main subject of the conference is the development of intelligent software systems and their application in industry and other fields. This conference was held in Ulyanovsk, Russia, October 23-25, 2018 (http://fti.ulstu.ru). The conference was supported by the Russian Association of Artificial Intelligence and the Russian Association of Fuzzy Systems and Soft Computing. More than thirty in-person reports were presented on the following topics: Applied Intelligent Systems, Intelligent Systems in the industry, Semantic systems and technologies in design, Data mining. The following problems were touched: application of intelligent data processing methods in industry, use of models and algorithms of the theory of fuzzy systems in applied developments.

Chapters
Exploring Bayesian belief network for risky behavior modelling: discretization and latent variables
Suvorova A., , in: CEUR Workshop ProceedingsVol. 2258: Proceedings of the II International Scientific and Practical Conference “Fuzzy Technologies in the Industry – FTI 2018”.: Ulyanovsk: CEUR Workshop Proceedings, 2018. P. 63–70.
Decision making in many areas is based on data about individual behavior often measured using different surveys. The study investigates the proposed approach for behavior modelling on the base of Bayesian belief networks that allows predicting behavior characteristics using small and incomplete data from surveys about behavior episodes. We explored the characteristics of the models ...
Added: February 10, 2020
Priority areas: IT and mathematics
Language: English
Keywords: fuzzy systems
CEUR Workshop Proceedings
Similar publications
ML-based Fast Simulation of FARICH Responses
Shipilov F., Barnyakov A., Ivanov A. et al., / Series Physics "arxiv.org". 2026.
A fast simulation of the detector response is a vital task in high-energy physics (HEP). Traditional Monte-Carlo methods form the backbone of modern particle physics simulation software but are computationally expensive. We present a machine-learning-based approach to fast simulation of the Focusing Aerogel Ring Imaging Cherenkov (FARICH) detector response. Given a particle track and momentum, ...
Added: May 19, 2026
Natural hazard database from Internet publications: text mining with a large language model
Derkacheva A., Sakirkina M., Kraev G. et al., /. 2026.
Comprehensive data on natural hazards and their consequences are crucial for effective for risk assessment, adaptation planning, and emergency response. However, many countries face challenges with fragmented, inconsistent, and inaccessible data, particularly regarding local-scale events. To address this data gap in Russia, we developed an end-to-end processing pipeline that scrapes news from various online sources, ...
Added: April 28, 2026
Algorithmic overlaps as thermodynamic variables: from local to cluster Monte Carlo dynamics in critical phenomena
Pilé I., Deng Y., Shchur L., / Series arXiv "math". 2026. No. 2604.10254.
We investigate the spatial overlap of successive spin configurations in Markov chain Monte Carlo simulations using the local Metropolis algorithm and the Svendsen-Wang and Wolff cluster algorithms. We examine the dynamics of these algorithms for two models in different universality classes: the Ising model and the Potts model with three components. The overlap of two ...
Added: April 20, 2026
Using predefined vector systems to speed up neural network multimillion class classification
Gabdullin N., Androsov I., / Series Computer Science "arxiv.org". 2026.
Label prediction in neural networks (NNs) has O(n) complexity proportional to the number of classes. This holds true for classification using fully connected layers and cosine similarity with some set of class prototypes. In this paper we show that if NN latent space (LS) geometry is known and possesses specific properties, label prediction complexity can ...
Added: April 2, 2026
Iterative Ricci-Foster Curvature Flow with GMM-Based Edge Pruning: A Novel Approach to Community Detection
Sorokin K., Beketov M., Онучин А. et al., / arxiv.org. Серия cs.SI "Social and Information Networks ". 2025.
Community detection in complex networks is a fundamental problem, open to new approaches in various scientific settings. We introduce a novel community detection method, based on Ricci flow on graphs. Our technique iteratively updates edge weights (their metric lengths) according to their (combinatorial) Foster version of Ricci curvature computed from effective resistance distance between the ...
Added: January 15, 2026
Implementing Transport Coding in OMNeT++ for Message Delay Reduction
Petrovanov I., Sergeev A., / Series Computer Science "arxiv.org". 2025. No. 2512.18332.
Transport coding reduces message delay in packet-switched networks by introducing controlled redundancy at the transport layer:  original packets are encoded into  coded packets, and the message is reconstructed after the first  successful deliveries, effectively shifting latency from the maximum packet delay to the -th order statistic. We present a concise, reproducible discrete-event implementation of transport coding in OMNeT++, including ...
Added: December 24, 2025
Hessian-based lightweight neural network for brain vessel segmentation on a minimal training dataset
Меньшиков И. А., Бернадотт А. К., Elvimov N. S., / Series arXie "Statistical mechanics". 2025.
Accurate segmentation of blood vessels in brain magnetic resonance angiography (MRA) is essential for successful surgical procedures, such as aneurysm repair or bypass surgery. Currently, annotation is primarily performed through manual segmentation or classical methods, such as the Frangi filter, which often lack sufficient accuracy. Neural networks have emerged as powerful tools for medical image ...
Added: December 1, 2025
Determining the boundary of dynamical chaos in the generalized Chirikov map via machine learning
Chernyshov D., Satanin A., Shchur L., / Series arXiv "math". 2025.
We investigate the boundary separating regular and chaotic dynamics in the generalized Chirikov map, an extension of the standard map with phase-shifted secondary kicks. Lyapunov maps were computed across the parameter space (K,K(α, τ)) and used to train a convolutional neural network (ResNet18) for binary classification of dynamical regimes. The model reproduces the known critical ...
Added: November 21, 2025
Эффективный алгоритм торговли на фондовом рынке: ретроспективный анализ, основанный на данных по S&P-500.
Rubchinskiy A., Chubarova D., / Series WP7 "Математические методы анализа решений в экономике, бизнесе и политике". 2025. No. WP7/2025/01.
The article examines one of the most famous examples of socio-economic systems, characterized by significant uncertainty – the S&P-500 stock market, where shares of 500 largest US companies are traded. No assumptions are made about the probabilistic characteristics of the stock market. A flexible algorithm for daily trading has been developed, based on both known fixed data ...
Added: November 9, 2025
Diffusion on language model embeddings for protein sequence generation
Meshchaninov V., Strashnov, P., Shevtsov A. et al., / Cornell University. Серия CoRR, arXiv:2403.03726 "Computing Research Repository,". 2025.
Protein design requires a deep understanding of the inherent complexities of the protein universe. While many efforts lean towards conditional generation or focus on specific families of proteins, the foundational task of unconditional generation remains underexplored and undervalued. Here, we explore this pivotal domain, introducing DiMA, a model that leverages continuous diffusion on embeddings derived ...
Added: October 5, 2025
Smoothie: Smoothing Diffusion on Token Embeddings for Text Generation
Shabalin A., Meshchaninov V., Vetrov D., / Series cs.CL, arXiv:2505.18853 "Computation and Language". 2025.
Diffusion models have achieved state-of-the-art performance in generating images, audio, and video, but their adaptation to text remains challenging due to its discrete nature. Prior approaches either apply Gaussian diffusion in continuous latent spaces, which inherits semantic structure but struggles with token decoding, or operate in categorical simplex space, which respect discreteness but disregard semantic ...
Added: October 5, 2025
A Feature Engineering Framework for Computer Vision Based on Topological Data Analysis
Абрамов А. С., Chernyshev V. L., Mikhaylets E. et al., / Series Social Science Research Network "Social Science Research Network". 2025.
Computer vision is one of the most relevant modern research areas with broad practical applications. However, traditional solutions based on deep learning have signicant limitations and can be misleading. Topological data analysis, on the other hand, is a modern approach to solving similar problems using mathematically deterministic methods of algebraic topology that reduce the risk ...
Added: September 23, 2025
On the construction of frieze patterns from partitions of convex polygons by nonintersecting diagonals
Kochetkov Y., / Series arXiv.org e-print archive "arXiv.math". 2025. No. 07600.
We demonstrate in an elementary way how to construct a frieze pattern of width m-3 from a partition of a convex m-gon by not intersecting diagonals. ...
Added: September 17, 2025
Применение моделей, основанных на нечеткой логике, к финансовым временным рядам
Shvedov A. S., Sviyazov V., В кн.: Системное моделирование социально-экономических процессов: труды 46-ой международной научной школы-семинара, г. Уфа, 9 - 15 октября 2023 г.: Воронеж: Истоки, 2024. С. 526–531.
The generalized autoregressive conditional heteroscedasticity model is widely applied to financial time series. There are further generalizations of this model. One of such generalizations is a combination of Takagi–Sugeno type fuzzy systems and autoregressive conditional heteroscedasticity models. The Takagi–Sugeno fuzzy systems advantage is that there is a standalone generalized autoregressive conditional heteroscedasticity model constructed for ...
Added: June 26, 2024
Fuzzy Volatility Models with Application to the Russian Stock Market
Sviyazov V., Control Sciences 2022 No. 6 P. 21–28
Volatility modeling and forecasting is a topical problem both in scientific circles and in the practice. This paper develops an approach combining the GARCH model and fuzzy logic. The Takagi–Sugeno fuzzy inference scheme is adopted to fuzzify an original autoregression model (the conditional heteroskedasticity model). As a result, several different local GARCH models can be ...
Added: December 6, 2023
Существует ли эффект выходного дня: исследование российского фондового рынка с помощью нечетких систем
Sviyazov V., Экономический журнал Высшей школы экономики 2023 Т. 27 № 3 С. 412–434
The problem of volatility forecasting with and without consideration of weekly seasonality effect (the weekend effect) is examined in this research. The question of the seasonality existence is understood in the following sense: do models, which incorporate seasonality, feature better forecasts? The fuzzy GARCH model, which accounts for a weekly seasonality effect is presented in ...
Added: October 28, 2023
Intelligent and Fuzzy Systems. Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference, Volume 1.
Cham: Springer, 2023.
This book consists of the papers accepted after a careful review process at an international scientific meeting where the latest developments on intelligent and fuzzy systems are presented and discussed. The latest developments in both the theoretical and practical fields of the new fuzzy set extensions have been prepared by expert researchers. Contributed by participants ...
Added: September 12, 2023
The 10th International Conference on Integrated Models and Soft Computing in Artificial Intelligence (IMSC-2021). Kolomna
[б.и.], 2021.
Added: November 10, 2021
Frontiers in Artificial Intelligence and Applications
IOS Press, 2021.
Fuzzy systems and data mining are indispensible aspects of the computer systems and algorithms on which the world has come to depend. This book presents papers from FSDM 2021, the 7th International Conference on Fuzzy Systems and Data Mining. The conference, originally due to take place in Seoul, South Korea, was held online on 26-29 October ...
Added: October 29, 2021
A decision support system for prescription of non-medication-based rehabilitation
Gorbunov I. V., Zaitsev A. A., Meshcheryakov R. V. et al., Biomedical engineering 2017 Vol. 5 No. 50 P. 393–397
The construction of a recommendation system for selecting one of five non-medication-based rehabilitation complexes for participants in armed conflicts and emergencies is described. Rehabilitation techniques developed at the Tomsk Science Research Institute of Balneology and Physiotherapy prevent potential chronicization of pathological processes, increase the body’s adaptive reserves, and improve quality of life in those affected ...
Added: September 27, 2021
Tradeoff search methods between interpretability and accuracy of the identification fuzzy systems based on rules
Yankovskaya A. E., Gorbunov I. V., Hodashinsky I. A., Pattern Recognition and Image Analysis 2021 Vol. 2 No. 27 P. 243–265
This paper starts a brief historical overview of occurrence and development of fuzzy systems and their applications. Integration methods are proposed to construct a fuzzy system using other AI methods, achieving synergy effect. Accuracy and interpretability are selected as main properties of rule-based fuzzy systems. The tradeoff between interpretability and accuracy is considered to be ...
Added: September 27, 2021
О вейвлет-преобразованиях при моделировании цен акций нечеткими системами
Бричикова А. П., Mogilevich E., Shvedov A. S., Экономический журнал Высшей школы экономики 2019 Т. 23 № 3 С. 444–464
Models for time series are very important for the stock market. Fuzzy Takagi – Sugeno models (functional fuzzy systems) are a promising and already common approach, in which different regression dependencies are used for different areas of variation of certain parameters, and soft switching is performed using the fuzzy logic rules. This is the advantage ...
Added: February 18, 2020
Fuzzy Systems (FUZZ-IEEE), IEEE International Conference Proceedings
IEEE, 2019.
Added: October 30, 2019
Atlantis Studies in Uncertainty Modelling, Proceedings of the 2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology (EUSFLAT 2019)
Atlantis Press, 2019.
The 11th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT 2019), will take place in Prague, the capital of the Czech Republic on September 9-13, 2019. The main organizer of the conference is the Institute for Research and Applications of Fuzzy Modeling (IRAFM), University of Ostrava and the Czech Institute of Informatics, ...
Added: August 21, 2019
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