Triclusters of Close Values for the Analysis of 3D Data

Дистиллированные кисломолочные напитки встречаются в пищевой промышленности редко, несмотря на повсеместное распространение растительных спиртных напитков. В настоящее время производство крепких дистиллированных алкогольных напитков из кисломолочных продуктов с использованием традиционных технологий известно лишь среди монголоязычных народов и их сибирских соседей. Данное исследование представляет собой первый междисциплинарный анализ дарасуна, традиционного бурятского спиртного напитка, изготавливаемого из кисломолочного напитка ...

Добавлено: 10 июня 2026 г.

Artificial intelligence and digital twins for failure prediction in data center cooling systems: a comprehensive literature review (2018–2026)

Гущин М. И., Butorova A., Bobakov V. и др., European Physical Journal: Special Topics 2026 P. 1–19

Добавлено: 10 июня 2026 г.

Innovations in Information and Decision Sciences. Proceedings of the 13th International Conference on Frontiers in Intelligent Computing: Theory and Applications (FICTA 2025), Volume 4

Springer, 2026.

Добавлено: 8 июня 2026 г.

Wave dynamics within the Whitham-Ostrovsky equation

Flamarion M. V., Пелиновский Е. Н., Nonlinear Dynamics 2026 Vol. 114 Article 784

Добавлено: 5 июня 2026 г.

Is Canfield Right? On the Asymptotic Coefficients for the Maximum Antichain of Partitions and Related Counting Inequalities

Игнатов Д. И., , in: 11th International Conference, AIST 2023, Yerevan, Armenia, September 28–30, 2023, Revised Selected Papers. Analysis of Images, Social Networks and Texts. Lecture Notes in Computer Science (LNCS, volume 14486).: Cham: Springer, 2024. P. 349 – 361.

Добавлено: 23 января 2026 г.

Object-Attribute Biclustering for Elimination of Missing Genotypes in Ischemic Stroke Genome-Wide Data

Игнатов Д. И., Khvorykh G., Khrunin A. и др., , in: Recent Trends in Analysis of Images, Social Networks and Texts. 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020 Revised Supplementary ProceedingsVol. 12602.: Springer, 2021. P. 185–204.

Добавлено: 1 ноября 2022 г.

Proceedings of the Fifthteenth International Conference on Concept Lattices and Their Applications

CEUR-WS.org, 2020.

Добавлено: 30 октября 2020 г.

CLA 2018: The 14th International Conference on Concept Lattices and Their Applications

CEUR Workshop Proceedings, 2018.

Добавлено: 25 ноября 2018 г.

Multimodal Clustering for Community Detection

Игнатов Д. И., Семенов А. В., Комиссарова Д. В. и др., , in: Formal Concept Analysis of Social Networks.: Springer, 2017. Ch. 4 P. 59–96.

Добавлено: 17 декабря 2017 г.

Formal Concept Analysis for Knowledge Discovery. Proceedings of International Workshop on Formal Concept Analysis for Knowledge Discovery (FCA4KD 2017), Moscow, Russia, June 1, 2017.

CEUR-WS.org, 2017.

Добавлено: 4 октября 2017 г.

On Containment of Triclusters Collections Generated by Quantified Box Operators

Егурнов Д. А., Игнатов Д. И., MEPHU NGUIFO E., , in: 23rd International Symposium on Methodologies for Intelligent Systems - Proceedings.: Birkhauser/Springer, 2017. P. 573–579.

Добавлено: 18 сентября 2017 г.

Query-Based Versus Tree-Based Classification: Application to Banking Data

Масютин А. А., Кашницкий Ю. С., , in: Foundations of Intelligent Systems.: Warsz.: Springer, 2017. P. 664–673.

The cornerstone of retail banking risk management is the estimation of the expected losses when granting a loan to the borrower. The key driver for loss estimation is probability of default (PD) of the borrower. Assessing PD lies in the area of classification problem. In this paper we apply FCA query-based classification techniques to Kaggle ...

Добавлено: 6 июля 2017 г.

Mining Triclusters of Similar Values in Triadic Real-Valued Contexts

Егурнов Д. А., Игнатов Д. И., MEPHU NGUIFO E., , in: 14th International Conference on Formal Concept Analysis - Supplementary Proceedings.: University Rennes 1, 2017. P. 31–47.

Добавлено: 21 июня 2017 г.

14th International Conference on Formal Concept Analysis - Supplementary Proceedings

University Rennes 1, 2017.

This volume is the supplementary volume of the 14th International Conference on Formal Concept Analysis (ICFCA 2017), held from June 13th to 16th 2017, at IRISA, Rennes. The ICFCA conference series is one of the major venues for researches from the field of Formal Concept Analysis and related areas to present and discuss their recent ...

Добавлено: 19 июня 2017 г.

Approximate clusters, biclusters and n-clusters in the analysis of binary and general data matrices

Миркин Б. Г., , in: CLA 2016: Proceedings of the Thirteenth International Conference on Concept Lattices and Their Applications. CEUR Workshop ProceedingsVol. 1624.: M.: Higher School of Economics, National Research University, 2016. P. 7–8.

Аpproximate cluster structures are those of formal concepts and n-concepts with added numerical intensity weights. The talk presents theoretical results and computational methods for approximate clustering and n-clustering as extensions of the algebraic-geometrical properties of numerical matrices (SVD and the like) to the situations where one or most of elements of the solutions to be ...

Добавлено: 3 марта 2017 г.

Dualization in lattices given by ordered sets of irreducibles

Бабин М. А., Кузнецов С. О., Theoretical Computer Science 2017 Vol. Volume 658, Part B No. 7 January P. 316–326

Dualization of a monotone Boolean function on a finite lattice can be represented by transforming the set of its minimal 1 values to the set of its maximal 0 values. In this paper we consider finite lattices given by ordered sets of their meet and join irreducibles (i.e., as a concept lattice of a formal ...

Добавлено: 9 февраля 2017 г.

A Lattice-based Consensus Clustering Algorithm

Бочаров А. А., Гнатышак Д. В., Игнатов Д. И. и др., , in: CLA 2016: Proceedings of the Thirteenth International Conference on Concept Lattices and Their Applications. CEUR Workshop ProceedingsVol. 1624.: M.: Higher School of Economics, National Research University, 2016. P. 45–56.

Добавлено: 24 октября 2016 г.

On Stability of Triadic Concepts

Кузнецов С. О., Махалова Т. П., , in: CLA 2016: Proceedings of the Thirteenth International Conference on Concept Lattices and Their Applications. CEUR Workshop ProceedingsVol. 1624.: M.: Higher School of Economics, National Research University, 2016. P. 245–253.

Добавлено: 11 октября 2016 г.

Interval Pattern Concept Lattice as a Classifier Ensemble

Кашницкий Ю. С., Кузнецов С. О., , 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 ...

Добавлено: 6 октября 2016 г.

Proceedings of the International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI at ECAI 2016)

M.: [б.и.], 2016.

The four preceding editions of the FCA4AI Workshop showed that many researchers working in Artificial Intelligence are deeply interested by a well-founded method for classi- fication and mining such as Formal Concept Analysis (see http://www.fca4ai.hse.ru/). The first edition of FCA4AI was co-located with ECAI 2012 in Montpellier, the second one with IJCAI 2013 in Beijing, ...

Добавлено: 6 октября 2016 г.

Global Optimization in Learning with Important Data: an FCA-Based Approach

Кашницкий Ю. С., Кузнецов С. О., , in: CLA 2016: Proceedings of the Thirteenth International Conference on Concept Lattices and Their Applications. CEUR Workshop ProceedingsVol. 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 ...

Добавлено: 6 октября 2016 г.