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DTSTART;TZID=Asia/Seoul:20210216T163000
DTEND;TZID=Asia/Seoul:20210216T173000
DTSTAMP:20260419T100809
CREATED:20210205T012237Z
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UID:3594-1613493000-1613496600@dimag.ibs.re.kr
SUMMARY:Martin Ziegler\, Quantitative Coding and Complexity Theory of Continuous Data
DESCRIPTION:Specifying a computational problem requires fixing encodings for input and output: encoding graphs as adjacency matrices\, characters as integers\, integers as bit strings\, and vice versa. For such discrete data\, the actual encoding is usually straightforward and/or complexity-theoretically inessential (up to polynomial time\, say). \nBut concerning continuous data\, already real numbers naturally suggest various encodings with very different computational properties. \nWe recall the existing qualitative theory of computably ‘sensible’ encodings of topological spaces; and we newly develop the quantitative theory of complexity-theoretically ‘sensible’ encodings of metric spaces. \nJoint work with Donghyun Lim.
URL:https://dimag.ibs.re.kr/event/2021-02-16/
LOCATION:Room B232\, IBS (기초과학연구원)
CATEGORIES:Discrete Math Seminar
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