DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Ziegler, Martin | - |
dc.contributor.advisor | 마틴 지글러 | - |
dc.contributor.author | Lee, Hyunwoo | - |
dc.date.accessioned | 2021-05-13T19:32:29Z | - |
dc.date.available | 2021-05-13T19:32:29Z | - |
dc.date.issued | 2020 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=911006&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/284675 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 전산학부, 2020.2,[iii, 17 p. :] | - |
dc.description.abstract | Randomization is a very powerful tool which can reduce the complexity of a lot of algorithms in practice. However, to implement a randomized algorithm, sampling procedure from the fixed probability distribution is essential. In this paper, we formalized the sampling procedure from continuous probability distribution in the sense of Type-2 Theory of Effectivity which is theoretical framework to handle the computation over continuous data. We first show that every Borel probability measure on second countable $T_0$ spaces is just a push-forward measure of Canonical probability measure on Cantor Space. This is the extension of the result by Simpson and Schr$\ddot{o}$der, 2006. Second result is concerned with Brownian motion as the probability measure on the space of continuous function $f$ :[0,1]-> $\mathbb{R}$ with $f$(0)=0. We figure out the condition when such a measure can be sampled. This measure can be sampled if and only if its family of modulus of continuity can be sampled. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Computable Analysis▼aType-2 Theory of Effectivity▼aRandom sampling▼aProbability Theory▼aRandom Variable▼aWiener Process▼aBrownian motion | - |
dc.subject | 계산 해석학▼a유형-2 계산이론▼a확률추출▼a확률론▼a확률변수▼a위너 확률과정▼a브라운 운동 | - |
dc.title | Random sampling of continuous objects | - |
dc.title.alternative | 브라운 운동을 포함한 연속적 객체 확률추출의 계산가능성 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :전산학부, | - |
dc.contributor.alternativeauthor | 이현우 | - |
dc.title.subtitle | can we computably generate brownian motions? | - |
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