Desingularization of bounded-rank matrix sets

Valentin Khrulkov, Ivan Oseledets

    Результат исследований: Вклад в журналСтатьярецензирование

    4 Цитирования (Scopus)


    The conventional ways to solve optimization problems on low-rank matrix sets which appear in a great number of applications tend to ignore its underlying structure of an algebraic variety and existence of singular points. This leads to the appearance of inverses of singular values in algorithms and since they could be close to 0 it causes certain problems. We tackle this problem by utilizing ideas from algebraic geometry and show how to desingularize these sets. Our main result is an algorithm which uses only bounded functions of singular values and hence does not suffer from the issue described above.

    Язык оригиналаАнглийский
    Страницы (с-по)451-471
    Число страниц21
    ЖурналSIAM Journal on Matrix Analysis and Applications
    Номер выпуска1
    СостояниеОпубликовано - 2018


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