Better optimization algorithms, moving beyond the classics
Abstract/Contents
- Abstract
- This thesis studies several problems in optimization, from complexity-theoretic investigations to algorithm design questions. More specifically, (1) we give an iteration complexity-optimal algorithm for minimizing highly smooth convex function with Lipschitz continuous higher-order derivatives; (2) we investigate the complexity of optimizing convex, non-smooth functions with a highly parallel oracle, giving an algorithm with improved depth compared to the state-of-the-art and obtaining tighter lower bound characterizing when the parallel information helps compared to its fully sequential counterpart; (3) we propose an efficient sketching-based distributed algorithm with lightweight communication that can return high-accuracy solution for problem having composite structure. Through a better understanding of the fundamental barrier to problem efficiency on one hand, and the design of practical algorithms addressing requirement of modern computation model on the other, the thesis offers glimpse of the vast opportunities that the role of optimization remains to play for data science in either direction
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 | 2021; ©2021 |
| Publication date | 2021; 2021 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Jiang, Qijia |
|---|---|
| Degree supervisor | Candès, Emmanuel J. (Emmanuel Jean) |
| Thesis advisor | Candès, Emmanuel J. (Emmanuel Jean) |
| Thesis advisor | Pilanci, Mert |
| Thesis advisor | Wootters, Mary |
| Degree committee member | Pilanci, Mert |
| Degree committee member | Wootters, Mary |
| Associated with | Stanford University, Department of Electrical Engineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Qijia Jiang |
|---|---|
| Note | Submitted to the Department of Electrical Engineering |
| Thesis | Thesis Ph.D. Stanford University 2021 |
| Location | https://purl.stanford.edu/yw746kn3833 |
Access conditions
- Copyright
- © 2021 by Qijia Jiang
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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