LDR | | 01707nam u200421 4500 |
001 | | 000000418049 |
005 | | 20190215162530 |
008 | | 181129s2018 |||||||||||||||||c||eng d |
020 | |
▼a 9780438350830 |
035 | |
▼a (MiAaPQ)AAI10823599 |
035 | |
▼a (MiAaPQ)umn:19205 |
040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
082 | 0 |
▼a 658 |
100 | 1 |
▼a Li, Xiaobo. |
245 | 10 |
▼a Convex Optimization and Online Learning: Their Applications in Discrete Choice Modeling and Pricing. |
260 | |
▼a [S.l.]:
▼b University of Minnesota.,
▼c 2018. |
260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2018. |
300 | |
▼a 141 p. |
500 | |
▼a Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B. |
500 | |
▼a Advisers: Shuzhong Zhang |
502 | 1 |
▼a Thesis (Ph.D.)--University of Minnesota, 2018. |
520 | |
▼a The discrete choice model has been an important tool to model customers' demand when facing a set of substitutable choices. The random utility model, which is the most commonly used discrete choice framework, assumes that the utility of each alt |
590 | |
▼a School code: 0130. |
650 | 4 |
▼a Industrial engineering. |
650 | 4 |
▼a Operations research. |
650 | 4 |
▼a Applied mathematics. |
690 | |
▼a 0546 |
690 | |
▼a 0796 |
690 | |
▼a 0364 |
710 | 20 |
▼a University of Minnesota.
▼b Industrial and Systems Engineering. |
773 | 0 |
▼t Dissertation Abstracts International
▼g 80-01B(E). |
773 | |
▼t Dissertation Abstract International |
790 | |
▼a 0130 |
791 | |
▼a Ph.D. |
792 | |
▼a 2018 |
793 | |
▼a English |
856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14998583
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
980 | |
▼a 201812
▼f 2019 |
990 | |
▼a ***1012033 |