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Community Detection: Fundamental Lim...

Zhang, Ye.

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Community Detection: Fundamental Limits, Methodology, and Variational Inference.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Community Detection: Fundamental Limits, Methodology, and Variational Inference./
Author:	Zhang, Ye.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
Description:	94 p.
Notes:	Source: Dissertations Abstracts International, Volume: 80-02, Section: B.
Contained By:	Dissertations Abstracts International80-02B.
Subject:	Statistics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10957347
ISBN:	9780438273924

Community Detection: Fundamental Limits, Methodology, and Variational Inference.
Zhang, Ye.

Community Detection: Fundamental Limits, Methodology, and Variational Inference. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 94 p.

Source: Dissertations Abstracts International, Volume: 80-02, Section: B.

Thesis (Ph.D.)--Yale University, 2018.

This item must not be added to any third party search indexes.

Network analysis has become one of the most active research areas over the past few years. A core problem in network analysis is community detection. In this thesis, we investigate it under Stochastic Block Model and Degree-corrected Block Model from three different perspectives: 1) the minimax rates of community detection problem, 2) rate-optimal and computationally feasible algorithms, and 3) computational and theoretical guarantees of variational inference for community detection.

ISBN: 9780438273924Subjects--Topical Terms:

517247
Statistics.

Community Detection: Fundamental Limits, Methodology, and Variational Inference.
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245 1 0 $a Community Detection: Fundamental Limits, Methodology, and Variational Inference.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2018
300 $a 94 p.
500 $a Source: Dissertations Abstracts International, Volume: 80-02, Section: B.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Zhou, Harrison H.
502 $a Thesis (Ph.D.)--Yale University, 2018.
506 $a This item must not be added to any third party search indexes.
506 $a This item must not be sold to any third party vendors.
520 $a Network analysis has become one of the most active research areas over the past few years. A core problem in network analysis is community detection. In this thesis, we investigate it under Stochastic Block Model and Degree-corrected Block Model from three different perspectives: 1) the minimax rates of community detection problem, 2) rate-optimal and computationally feasible algorithms, and 3) computational and theoretical guarantees of variational inference for community detection.
590 $a School code: 0265.
650 4 $a Statistics. $3 517247
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710 2 $a Yale University. $3 515640
773 0 $t Dissertations Abstracts International $g 80-02B.
790 $a 0265
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792 $a 2018
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10957347