Comparison of Machine Learning Methods for Life Trajectory Analysis in Demography

The article presents an experimental study at the intersection of social anthropology and qualitative sociology. The empirical basis is a corpus of 18 short biographical sketches of collective farm peasant women from the village of Vysheley, Penza Region, created at the end of the Soviet period by school local historians and discovered by one of the authors during a ...

Added: October 7, 2026

Enhancing Boundary Stability in Decision Trees and Random Forests: A Weighted Sample Duplication Approach

Konstantinov A., Elizarova Anastasiya P., Utkin L., Computing, Telecommunications and Control 2026 Vol. 19 No. 1 P. 16–25

Decision trees and their ensemble extensions, such as random forests, are widely used as classification models due to their simplicity and interpretability. However, in many real-world tasks where class labels overlap in the feature space, standard decision trees rely on hard splits that create fragile decision boundaries. In these regions, small perturbations in the input ...

Added: October 2, 2026

Optimization of List-Based Reed-Solomon Decoding via Deep Learning

Portnoy S., Efremov A., Voloshin A., , in: 2026 Systems of Signal Synchronization, Generating and Processing in Telecommunications (SYNCHROINFO).: Petrozavodsk: IEEE, 2026. P. 1–4.

This paper presents a deep learning-based optimization of a list-decoding algorithm for a concatenated Hamming-Reed-Solomon code transmitted over an AWGN channel with BPSK modulation. The proposed method reformulates early termination of the erasure-pattern list as a weighted regression problem, addressing class imbalance through an asymmetric Weighted Mean Squared Error (WMSE) loss function that penalizes index ...

Added: October 1, 2026

A Model Based on Universal Filters for Image Color Correction

Aleksei Samarin, Nazarenko A., Alexander Savelev et al., Pattern Recognition and Image Analysis 2024 Vol. 34 No. 3 P. 844–854

Improving image quality is becoming an increasingly popular task, especially when working with mobile devices. One common approach to image enhancement is the use of convolutional neural networks. However, to achieve good results, such networks must be large enough, otherwise there is a risk of unwanted artifacts. In addition, large convolutional neural networks require significant ...

Added: September 21, 2026

Filter-Based Preprocessing Neural Network Model for Microorganism Detection Improvement

Aleksei Samarin, Aleksei Toropov, Alexander Savelev et al., , in: Pattern Recognition. ICPR 2024 International Workshops and Challenges. Kolkata, India, December 1, 2024, Proceedings, Part III. LNCS, volume 15616.: Cham: Springer, 2025. P. 308–320.

This research explores an innovative approach to enhancing the accuracy of detecting small microorganisms in complex microscopic environments. Our study introduces a streamlined, hybrid image pre-processing model specifically designed to address the challenges of identifying diplococci in live microscopy of dynamic samples. By integrating pre-defined filtering techniques with predictive adjustments for optimal applicability, our method ...

Added: September 21, 2026

Модель глубокого обучения для автоматизированной интерпретации медицинских электрофизиологических данных

Lebedev O. B., Шмелева А. Г., Гежа Н. С., Информатика и автоматизация (Труды СПИИРАН) 2026 Т. 25 № 3 С. 720–750

This paper describes the development of a neural network model for automated analysis of medical data in electrophysiology based on deep learning methods. The relevance of this work stems from the growing need to improve the objectivity, speed, and accuracy of processing complex spatiotemporal signals, such as ECG or EEG. Convolutional neural networks (CNNs), which ...

Added: September 10, 2026

Scalable machine learning approach to disordered 𝑠-wave superconductors

Vyacheslav D. Neverov, Lukyanov A., Andrey V. Krasavin et al., Physical Review B: Condensed Matter and Materials Physics 2026 Vol. 113 No. 2 Article 024515

We develop a neural network approach to solve the self-consistent Bogoliubov-de Gennes equations in strongly disordered s-wave superconductors. The method accurately reproduces inhomogeneous gap distributions and generalizes to system sizes far larger than those used in training. It reduces computational scaling from O(N6 ) to O(N2), enabling quantitative analysis of percolation phenomena and the superconductor-insulator ...

Added: September 5, 2026

Studying or Children? Factors and Diversity of Event Sequences in Female Educational and Childbearing Trajectories

Anna Cherviakova, Gudkova T., Alla Makarentseva et al., Comparative Sociology 2026 Vol. 25 P. 446–474

This study examines the relationship between educational and reproductive choices and aims to establish whether they compete in the lives of young Russian women born in the 1990s. The authors use longitudinal data of the ‘Trajectories in Education and Carriers’ survey (2011–2021; panel sample N = 992) and successively apply sequence analysis, cluster analysis, and ...

Added: September 4, 2026

A unified frequency-domain framework for tilted slice localization and ischemic stroke detection

Khodadoust J., Kulikova S., Khodadoust F., Biomedical Signal Processing and Control 2027 Vol. 129 Article 111284

Acute ischemic stroke (AIS) analysis from two-dimensional (2D) clinical imaging is hindered by uncontrolled slice tilt and geometric inconsistencies that violate the assumptions of pose-agnostic deep learning (DL) models. This paper proposes a unified geometry-aware, frequency-domain framework for tilted slice localization and ischemic stroke segmentation that explicitly decouples pose estimation from lesion analysis. The method ...

Added: September 2, 2026

Proceedings of the 43rd International Conference on Machine Learning (ICML 2026)

Seul: PMLR, 2026.

Added: June 4, 2026

Образ СССР в социальной памяти поколений современной России и бывших советских республик

СПб.: Наукоемкие технологии, 2022.

Added: May 30, 2026

Stable On-the-Fly Learning for Dynamic Neural Networks With Delayed Inputs

Chertopolokhov V., Mukhamedov A., Bugriy G. et al., IEEE Access 2026 Vol. 14 P. 14369–14392

This study presents on-the-fly identification and multi-step prediction of nonlinear systems with delayed inputs using a dynamic neural network combined with a smooth projection onto ellipsoids. The projection enforces parameter constraints that guarantee stability, while a Lyapunov–Krasovskii analysis yields computable ultimate error bounds. Riccati-type matrix inequalities are derived, providing an efficient vectorization–projection–devectorization implementation suitable for ...

Added: May 22, 2026

Измерение ИИ-грамотности взрослых россиян: методика и результаты

Davydov S. G., Федоров В. В., Социологические исследования 2026 № 5 С. 141–147

Представлены результаты измерения ИИ-грамотности взрослого населения России. Исследование решает проблему отсутствия эмпирических данных о фактическом уровне владения компетенциями в сфере искусственного интеллекта среди граждан. Методика основана на самооценке владения пятью типами ИИ-инструментов по 5‑балльной шкале и последующем индексировании. Сбор информации осуществлен методом телефонного опроса (CATI) на общероссийской выборке проекта «ВЦИОМ–Спутник» (N = 1600). Выявлен уровень ...

Added: May 13, 2026

Аналитический обзор методов извлечения текстовых транскрипций из речевых высказываний

Ролинский С. О., Dvoynikova A., В кн.: Альманах научных работ молодых ученых Университета ИТМОТ. 2.: Университет ИТМО, 2022. С. 336–340.

В работе рассмотрены основные существующие подходы к автоматическому распознаванию речи, а также проводится сравнительный анализ открытых компьютерных систем распознавания речи. Для экспериментальных исследований эффективности работы рассматриваемых систем используется речевой корпус LibriSpeech. ...

Added: April 24, 2026

Влияние планировщика на обучение нейронных сетей в задаче верификации диктора

Dvoynikova A., Садикова А. А., В кн.: Сборник трудов X Конгресса молодых ученыхТ. 1.: Университет ИТМО, 2021.

В работе рассматривается применение различных планировщиков обучения (англ. scheduler) нейронных сетей для задачи текстонезависимой верификации дикторов. Для экспериментальных исследований использовалась база данных VoxCeleb1, которая содержит в себе различные речевые высказывания 1211 дикторов. В работе проводился анализ влияния различных планировщиков обучения нейронных сетей, представленных в библиотеке PyTorch языка программирования Python, а также 2 алгоритма планировщика, представленных ...

Added: April 24, 2026