MARC보기
LDR02141nmm uu200445 4500
001000000332527
00520240805170943
008181129s2018 |||||||||||||||||c||eng d
020 ▼a 9780438036444
035 ▼a (MiAaPQ)AAI10788077
035 ▼a (MiAaPQ)upenngdas:13167
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0820 ▼a 621.3
1001 ▼a Huang, Weiyu.
24510 ▼a Networked Data Analytics: Network Comparison and Applied Graph Signal Processing.
260 ▼a [S.l.] : ▼b University of Pennsylvania., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 255 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.
500 ▼a Adviser: Alejandro Ribeiro.
5021 ▼a Thesis (Ph.D.)--University of Pennsylvania, 2018.
520 ▼a Networked data structures has been getting big, ubiquitous, and pervasive. As our day-to-day activities become more incorporated with and influenced by the digital world, we rely more on our intuition to provide us a high-level idea and subconsc
520 ▼a We show that in order to formalize the intuitive idea to measure the difference between a pair of networks of arbitrary sizes, we could design two algorithms based on the intuition to find mappings between the node sets or to map one network int
520 ▼a In the context of data analytics on top of networks, we design domain-specific tools by leveraging the recent advances in graph signal processing, which formalizes the intuitive notion of smoothness and variation of signals defined on top of net
590 ▼a School code: 0175.
650 4 ▼a Electrical engineering.
650 4 ▼a Statistics.
650 4 ▼a Mathematics.
690 ▼a 0544
690 ▼a 0463
690 ▼a 0405
71020 ▼a University of Pennsylvania. ▼b Electrical and Systems Engineering.
7730 ▼t Dissertation Abstracts International ▼g 79-10B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0175
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14997435 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자