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Теоремы о редукции в теории коллективного выбора
Итоги науки и техники. Современная математика и ее приложения. Тематические обзоры. 2020. Т. 174. С. 46–51.
Polyakov N. L., Шамолин М. В.
In the paper, combinatorial theorems relating to the theory of social choice are obtained.These theorems describe general conditions under which theproblem on the preserving the preferencesetDby an arbitrary aggregation rulefand the problem on the compatibility of the preference setDwith a pair(f,C)can be reduced to similar problems for two specific aggregation rules: the majority rulemaj and the “counting rhyme” rule cog. Results are obtained within the framework ofclone approachin the theory of social choice proposed by S. Shelah and developed by the authors.
Language:
Russian
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Гомеоморфизмы топологических пространств называются эквивалентными по надстройке, если надстройки над ними топологически эквивалентны. В частности, топологически сопряженные гомеоморфизмы эквивалентны по надстройке. Известно, что для гомологически неприводимых гомеоморфизмов их топологическая сопряженность является необходимым и достаточным условием их эквивалентности по надстройке. Тогда как инварианты топологической сопряженности гомологически приводимых гомеоморфизмов во многих случаях являются избыточными для эквивалентности по ...
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Пусть M обозначает симметрическое пространство некомпактного типа ранга 1. Опираясь на фундаментальную работу [1], в [2] было показано, что плотность соответствующим образом нормированной суммы независимых Hn-значных случайных величин, определенная через сложение Мёбиуса в модели шара Пуанкаре, сходится к фундаментальному решению соответствующего уравнения теплопроводности. Пределом являлся нормальный закон на Hn, соответствующий ядру теплопроводности, определяемому оператором Лапласа–Бельтрами. ...
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М.: ООО «Адвансед солюшнз», 2026.
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Tyukin I., Tyukina T., van Helden D. P. et al., Information Sciences 2024 Vol. 678 Article 120856
AI errors pose a significant challenge, hindering real-world applications. This work introduces a novel approach to cope with AI errors using weakly supervised error correctors that guarantee a specific level of error reduction. Our correctors have low computational cost and can be used to decide whether to abstain from making an unsafe classification. We provide ...
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IEEE, 2026.
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