This decommissioned ERA site remains active temporarily to support our final migration steps to https://ualberta.scholaris.ca, ERA's new home. All new collections and items, including Spring 2025 theses, are at that site. For assistance, please contact erahelp@ualberta.ca.
Theses and Dissertations
This collection contains theses and dissertations of graduate students of the University of Alberta. The collection contains a very large number of theses electronically available that were granted from 1947 to 2009, 90% of theses granted from 2009-2014, and 100% of theses granted from April 2014 to the present (as long as the theses are not under temporary embargo by agreement with the Faculty of Graduate and Postdoctoral Studies). IMPORTANT NOTE: To conduct a comprehensive search of all UofA theses granted and in University of Alberta Libraries collections, search the library catalogue at www.library.ualberta.ca - you may search by Author, Title, Keyword, or search by Department.
To retrieve all theses and dissertations associated with a specific department from the library catalogue, choose 'Advanced' and keyword search "university of alberta dept of english" OR "university of alberta department of english" (for example). Past graduates who wish to have their thesis or dissertation added to this collection can contact us at erahelp@ualberta.ca.
Items in this Collection
- 3Supervised learning
- 2Machine learning
- 1Aboriginal identification
- 1Actor-critic
- 1Big data
- 1Cancer screening
-
Fall 2010
Performance and stability of many iterative algorithms such as stochastic gradient descent largely depend on a fixed and scalar step-size parameter. Use of a fixed and scalar step-size value may lead to limited performance in many problems. We study several existing step-size adaptation...
-
Spring 2014
Each patient with Type-1 diabetes must decide how much insulin to inject before each meal to maintain an acceptable level of blood glucose. The actual injection dose is based on a formula that takes current blood glucose level and the meal size into consideration. While following this insulin...
-
Public Health Applications Using Big Data and Machine Learning Methods: Name- and Location-based Aboriginal Ethnicity Classification and Sentiment Analysis of Breast Cancer Screening in the United States Using Twitter
DownloadFall 2017
Applications using big data and machine learning techniques are transforming how people live in the 21st century, however they are generally underutilized in public health compared to other domains. We proposed and conducted two independent studies to investigate how big data and machine learning...