Výsledky vyhledávání

Report

MLEM: Generative and Contrastive Learning as Distinct Modalities for Event Sequences

Autor: Moskvoretskii, Viktor, Osin, Dmitry, Shvetsov, Egor, Udovichenko, Igor, Zhelnin, Maxim, Dukhovny, Andrey, Zhimerikina, Anna, Burnaev, Evgeny

This study explores the application of self-supervised learning techniques for event sequences. It is a key modality in various applications such as banking, e-commerce, and healthcare. However, there is limited research on self-supervised learning f

Externí odkaz: http://arxiv.org/abs/2401.15935

Zobrazit plný text záznamu

Report

Maximum Relative Divergence Principle for Grading Functions on Direct Products of Chains

Autor: Dukhovny, Alexander

The concept of Shannon Entropy for probability distributions and associated Maximum Entropy Principle are extended here to the concepts of Relative Divergence of one Grading Function from another and Maximum Relative Divergence Principle for grading

Externí odkaz: http://arxiv.org/abs/2303.14261

Zobrazit plný text záznamu

Report

Maximum Relative Divergence Principle for Grading Functions on Power Sets

Autor: Dukhovny, Alexander

The concept of Relative Divergence of one Grading Function from another is extended from totally ordered chains to power sets of finite event spaces. Shannon Entropy concept is extended to normalized grading functions on such power sets. Maximum Rela

Externí odkaz: http://arxiv.org/abs/2207.07099

Zobrazit plný text záznamu

Akademický článek

Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.

Report

Axiomatic Origins of Mathematical Entropy: Grading Ordered Sets

Autor: Dukhovny, Alexander

Shannon's entropy and other entropy-based concepts are derived from the new, more general concept of relative divergence of one "grading' function on a linearly ordered set from another such function. The definition of relative divergence is derived

Externí odkaz: http://arxiv.org/abs/1903.05240

Zobrazit plný text záznamu

Akademický článek

Land cover change detection in the Aralkum with multi-source satellite datasets

Autor: Fabian Löw, Dimo Dimov, Shavkat Kenjabaev, Sherzod Zaitov, Galina Stulina, Viktor Dukhovny

Publikováno v: GIScience & Remote Sensing, Vol 59, Iss 1, Pp 17-35 (2022)

The Aral Sea, once the fourth largest freshwater lake on Earth, has lost circa 90% of its original water surface in 1960. Maps of different land cover categories provide a suitable baseline to plan and implement effective measures to combat ongoing d

Externí odkaz: https://doaj.org/article/c3ef8198bf454c5b8c91feacdd9a25f6