Leveraging game structure in modern optimization
Abstract/Contents
- Abstract
- First-order algorithms have risen in prominence in modern optimization, partly due to their successful application to problems in data science and machine learning, especially in settings with large dimensionality and dataset size. In this thesis, we focus on large-scale optimization problems with game structure, either explicitly or implicitly. By uncovering and leveraging such game structure, we design accelerated or randomized first-order algorithms which obtain nearly-linear or sublinear time for a wide range of fundamental decision making tasks. Towards achieving our results we take a modern twist on two classic optimization techniques, acceleration and randomization, demonstrating their versatile utility in modern algorithm design for game-structured optimization tasks.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2023; ©2023 |
| Publication date | 2023; 2023 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Jin, Yujia |
|---|---|
| Degree supervisor | Sidford, Aaron |
| Thesis advisor | Sidford, Aaron |
| Thesis advisor | Blanchet Mancilla, Jose |
| Thesis advisor | Ye, Yinyu |
| Degree committee member | Blanchet Mancilla, Jose |
| Degree committee member | Ye, Yinyu |
| Associated with | Stanford University, School of Engineering |
| Associated with | Stanford University, Department of Management Science and Engineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Yujia Jin. |
|---|---|
| Note | Submitted to the Department of Management Science and Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2023. |
| Location | https://purl.stanford.edu/tg158wd3408 |
Access conditions
- Copyright
- © 2023 by Yujia Jin
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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