Novel frameworks for auctions and optimization
Name
941161810-MIT.pdf
Description
Full printable version
Size
21.06 MB
Format
Adobe PDF
Checksum (MD5)
e058bb55a22b5be3242e129ce8e10165
Author(s)
Zhu, Zeyuan Allen
Advisor(s)
Jonathan A. Kelner and Silvio Micali.
Date Issued
2015
Publisher
Massachusetts Institute of Technology
Abstract
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.
Description
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).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
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