2022/2023
Топологическая обработка данных
Статус:
Дисциплина общефакультетского пула
Кто читает:
Факультет математики
Когда читается:
3, 4 модуль
Охват аудитории:
для всех кампусов НИУ ВШЭ
Преподаватели:
Горбунов Василий Геннадьевич
Язык:
английский
Кредиты:
6
Контактные часы:
72
Course Syllabus
Abstract
Topological Data Analysis (TDA) is a field that lies at the intersection of data analysis, algebraic
topology, computational geometry, computer science, statistics, and other related areas. The main goal of TDA
is to use ideas and results from geometry and topology to develop tools for studying qualitative features of
data. To achieve this goal, one needs precise definitions of qualitative features, tools to compute them in
practice, and some guaranteeabout the robustness of those features. One way to address all three points is a
method in TDA called persistent homology (PH). This method is appealing for applications because it is based
on algebraic topology, which gives a well-understood theoretical framework to study qualitative features of
data with complex structure, is computable via linear algebra, and is robust with respect to small perturbations
in input data