| LDR | | 00000nmm u2200205 4500 |
| 001 | | 000000333442 |
| 005 | | 20250115153650 |
| 008 | | 181129s2018 ||| | | | eng d |
| 020 | |
▼a 9780438325418 |
| 035 | |
▼a (MiAaPQ)AAI10822189 |
| 035 | |
▼a (MiAaPQ)berkeley:17999 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
| 049 | 1 |
▼f DP |
| 082 | 0 |
▼a 510 |
| 100 | 1 |
▼a Wilson, Ashia. |
| 245 | 10 |
▼a Lyapunov Arguments in Optimization. |
| 260 | |
▼a [S.l.] :
▼b University of California, Berkeley.,
▼c 2018 |
| 260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2018 |
| 300 | |
▼a 160 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B. |
| 500 | |
▼a Advisers: Michael I. Jordan |
| 502 | 1 |
▼a Thesis (Ph.D.)--University of California, Berkeley, 2018. |
| 520 | |
▼a Optimization is among the richest modeling languages in science. In statistics and machine learning, for instance, inference is typically posed as an optimization problem. While there are many algorithms designed to solve optimization problems, |
| 520 | |
▼a The central contributions of this thesis are the following results: we (1) present several variational principles whereby we obtain continuous-time dynamical systems useful for optimization |
| 590 | |
▼a School code: 0028. |
| 650 | 4 |
▼a Mathematics. |
| 690 | |
▼a 0405 |
| 710 | 20 |
▼a University of California, Berkeley.
▼b Statistics. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 80-01B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0028 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2018 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14998454
▼n KERIS |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a 관리자
▼b 관리자 |