MARC보기
LDR01707nam u200421 4500
001000000418049
00520190215162530
008181129s2018 |||||||||||||||||c||eng d
020 ▼a 9780438350830
035 ▼a (MiAaPQ)AAI10823599
035 ▼a (MiAaPQ)umn:19205
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 247004
0820 ▼a 658
1001 ▼a Li, Xiaobo.
24510 ▼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
5021 ▼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
71020 ▼a University of Minnesota. ▼b Industrial and Systems Engineering.
7730 ▼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
85640 ▼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