Explorations of Optimization Methods for Deep Learning with Examples from Various Applications

Graduate Project

Public Deposited

Citeable URL: https://ir.library.oregonstate.edu/concern/graduate_projects/xw42ng43c

Descriptions

Attribute Name	Values
Creator	Zhang, Nachuan
Abstract	This paper explores some optimization methods such as the gradient descent method, Gauss-Newton method, and stochastic gradient method. Some examples of minimizing objective functions are given to validate the theories. Then we introduce a simple example of artificial neural networks, define its structure, and apply the optimization methods to it. Finally we use an image classification example to end this expository paper.
Resource Type	Capstone Project
Date Issued	2021
Degree Level	Master's
Degree Name	Master of Science (M.S.)
Degree Field	Mathematics
Degree Grantor	Oregon State University
Commencement Year	2021
Advisor	Peszynska, Malgorzata
Committee Member	Showalter, Ralph Higdon, Robert
Academic Affiliation	Mathematics
Rights Statement	In Copyright
Publisher	Oregon State University
Peer Reviewed	No
Language	English [eng]
Embargo reason	Ongoing Research
Embargo date range	2021-07-13 to 2022-03-09

Thumbnail	Title	Date Uploaded	Visibility	Actions
	ZhangNachuan2021.pdf	2021-07-12	Public	Download