2026-09-19T08:53:33Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1015942026-06-16T18:17:37Zcom_1721.1_7582com_1721.1_7581col_1721.1_131022
Jonathan A. Kelner and Silvio Micali.
Zhu, Zeyuan Allen
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2016-03-03T21:11:05Z
2016-03-03T21:11:05Z
2015
2015
http://hdl.handle.net/1721.1/101594
941161810
Thesis: Sc. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 255-269).
This thesis contains two parts. Part I introduces novel frameworks for modeling uncertainty in auctions. This enables us to provide robust analysis to alternative specifications of preferences and information structures in Vickrey and VCG auctions. Part II introduces novel frameworks for understanding first-order methods in optimization. This enables us to (1) break 20-year barriers on the running time used for solving positive linear programs, (2) reduce the complexity for solving positive semidefinite programs, and (3) strengthen the theory of matrix multiplicative weight updates and improve the theory of linear-sized spectral sparsification.
by Zeyuan Allen-Zhu.
Sc.D.
269 pages
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Novel frameworks for auctions and optimization
Thesis
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