| LDR | | 00000nmm u2200205 4500 |
| 001 | | 000000330642 |
| 005 | | 20241104112804 |
| 008 | | 181129s2017 ||| | | | eng d |
| 020 | |
▼a 9780438097353 |
| 035 | |
▼a (MiAaPQ)AAI10891772 |
| 035 | |
▼a (MiAaPQ)OhioLINK:osu1503180139155502 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
| 049 | 1 |
▼f DP |
| 082 | 0 |
▼a 310 |
| 100 | 1 |
▼a Yan, Zhifei. |
| 245 | 10 |
▼a Semidefinite Programming Approaches to Network Clustering and Smoothing. |
| 260 | |
▼a [S.l.] :
▼b The Ohio State University.,
▼c 2017 |
| 260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2017 |
| 300 | |
▼a 111 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B. |
| 500 | |
▼a Adviser: Vincent Vu. |
| 502 | 1 |
▼a Thesis (Ph.D.)--The Ohio State University, 2017. |
| 520 | |
▼a Community detection and link prediction are two important problems in network analysis. In this dissertation, we propose semidefinite programming approaches to network community detection and edge probabilities estimation. Interestingly, despite |
| 520 | |
▼a For community detection, the SDP is derived from the partition criterion of maximizing the sum of average intra-cluster similarities over all clusters. The feasible set of our SDP is contained in the Fantope, which enables us to connect our SDP |
| 590 | |
▼a School code: 0168. |
| 650 | 4 |
▼a Statistics. |
| 690 | |
▼a 0463 |
| 710 | 20 |
▼a The Ohio State University.
▼b Statistics. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 79-10B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0168 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2017 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15000269
▼n KERIS |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a 관리자
▼b 관리자 |