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Regular version of the site
Article
Relative Chaoticity of Natural Languages

Yerbolova A. S., Tomashchuk K., Kogan A. et al.

Complexity. 2026. P. 1-34.

Book chapter
KoWit-24: A Richly Annotated Dataset of Wordplay in News Headlines

Alexander Baranov, Anna Palatkina, Makovka Y. et al.

In bk.: Proceedings of the 15th International Conference on Recent Advances in Natural Language Processing. Shumen: INCOMA Ltd, 2025. P. 125-132.

Working paper
Hessian-based lightweight neural network for brain vessel segmentation on a minimal training dataset

Меньшиков И. А., Бернадотт А. К., Elvimov N. S.

Statistical mechanics. arXie. arXive, 2025

The 8th Workshop "What can FCA do for artificial intelligence? (FCA4AI)"

On August 29 the International Laboratory for Intelligent Systems and Structural Analysis (ISSA) held the 8th Workshop "What can FCA do for artificial intelligence? (FCA4AI)"  as a part of the program of the European Conference on Artificial Intelligence (ECAI 2020).

This and the preceding editions of the FCA4AI Workshop (from ECAI 2012 until IJCAI 2019) showed that many researchers working in Artificial Intelligence are indeed interested by powerful techniques for classification and data mining provided by Formal Concept Analysis.
The workshop proceedings will be published as CEUR proceedings (see the preceding editions in CEUR Proceedings Vol-2529, Vol-2149, Vol-1703, Vol-1430, Vol-1257, Vol-1058, and Vol-939).
Program Co-chairs:
Sergei O. Kuznetsov (National Research University Higher Schools of Economics, Moscow, Russia)
Amedeo Napoli (Université de Lorraine, CNRS, Inria, LORIA, Nancy, France)
Sebastian Rudolph (Technische Universität Dresden, Germany)

"What can FCA do for artificial intelligence? (FCA4AI)" 
ECAI 2020