Event
01_1
제출번호(No.) | 0264 |
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분류(Section) | Invited Lecture |
분과(Session) | (AM) Applied Mathematics(including AI, Data Science) (AM) |
영문제목 (Title(Eng.)) |
De Giorgi's minimizing movements |
저자(Author(s)) |
Dohyun Kwon1 University of Seoul1 |
초록본문(Abstract) | The study of gradient flows holds significant importance across various fields, including partial differential equations, optimization, and machine learning. In this talk, we aim to explore the relationship between gradient flows and their time-discretized formulations, known as De Giorgi's minimizing movements scheme. We focus on how De Giorgi's minimizing movements coincide with gradient flows in two different spaces: the space of sets and the space of probability measures called Wasserstein space. Then, we discuss their implications for free boundary problems, optimal transport, and generative models. |
분류기호 (MSC number(s)) |
35K55, 35B40, 49J20, 49Q22 |
키워드(Keyword(s)) | Minimizing movements, gradient flows, optimal transport, optimization, Wasserstein distance |
강연 형태 (Language of Session (Talk)) |
Korean |