LDR | | 00000nmm u2200205 4500 |
001 | | 000000330825 |
005 | | 20241105113815 |
008 | | 181129s2018 ||| | | | eng d |
020 | |
▼a 9780438126077 |
035 | |
▼a (MiAaPQ)AAI10903001 |
035 | |
▼a (MiAaPQ)umichrackham:001244 |
040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
049 | 1 |
▼f DP |
082 | 0 |
▼a 510 |
100 | 1 |
▼a McMillan, Audra. |
245 | 10 |
▼a Differential Privacy, Property Testing, and Perturbations. |
260 | |
▼a [S.l.] :
▼b University of Michigan.,
▼c 2018 |
260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2018 |
300 | |
▼a 110 p. |
500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B. |
500 | |
▼a Adviser: Anna Catherine Gilbert. |
502 | 1 |
▼a Thesis (Ph.D.)--University of Michigan, 2018. |
520 | |
▼a Controlling the dissemination of information about ourselves has become a minefield in the modern age. We release data about ourselves every day and don't always fully understand what information is contained in this data. It is often the case t |
520 | |
▼a At its heart, this thesis is about the study of information. Many of the results can be formulated as asking a subset of the questions: does the data you have contain enough information to learn what you would like to learn? and how can I affect |
520 | |
▼a We begin with an information theoretic lower bound for graphon estimation. This explores the fundamental limits of how much information about the underlying population is contained in a finite sample of data. We then move on to exploring the con |
590 | |
▼a School code: 0127. |
650 | 4 |
▼a Mathematics. |
690 | |
▼a 0405 |
710 | 20 |
▼a University of Michigan.
▼b Mathematics. |
773 | 0 |
▼t Dissertation Abstracts International
▼g 79-12B(E). |
773 | |
▼t Dissertation Abstract International |
790 | |
▼a 0127 |
791 | |
▼a Ph.D. |
792 | |
▼a 2018 |
793 | |
▼a English |
856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15000509
▼n KERIS |
980 | |
▼a 201812
▼f 2019 |
990 | |
▼a 관리자
▼b 관리자 |