Browsing University of Waterloo by Subject "unsupervised learning"
Now showing items 1-10 of 10
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Automated Knowledge Discovery using Neural Networks
(University of Waterloo, 2021-05-21)The natural world is known to consistently abide by scientific laws that can be expressed concisely in mathematical terms, including differential equations. To understand the patterns that define these scientific laws, it ... -
BotChase: Graph-Based Bot Detection Using Machine Learning
(University of Waterloo, 2019-05-21)Bot detection using machine learning (ML), with network flow-level features, has been extensively studied in the literature. However, existing flow-based approaches typically incur a high computational overhead and do not ... -
Contributions to Unsupervised and Semi-Supervised Learning
(University of Waterloo, 2009-05-22)This thesis studies two problems in theoretical machine learning. The first part of the thesis investigates the statistical stability of clustering algorithms. In the second part, we study the relative advantage of ... -
Discovery and Analysis of Aligned Pattern Clusters from Protein Family Sequences
(University of Waterloo, 2014-04-28)Protein sequences are essential for encoding molecular structures and functions. Consequently, biologists invest substantial resources and time discovering functional patterns in proteins. Using high-throughput technologies, ... -
Improved Slow Feature Analysis for Process Monitoring
(University of Waterloo, 2022-08-22)Unsupervised multivariate statistical analysis models are valuable tools for process monitoring and fault diagnosis. Among them, slow feature analysis (SFA) is widely studied and used due to its explicit statistical ... -
Learning from Partially Labeled Data: Unsupervised and Semi-supervised Learning on Graphs and Learning with Distribution Shifting
(University of Waterloo, 2007-08-20)This thesis focuses on two fundamental machine learning problems:unsupervised learning, where no label information is available, and semi-supervised learning, where a small amount of labels are given in addition to unlabeled ... -
Likelihood-based Density Estimation using Deep Architectures
(University of Waterloo, 2019-12-20)Multivariate density estimation is a central problem in unsupervised machine learning that has been studied immensely in both statistics and machine learning. Several methods have thus been proposed for density estimation ... -
Robust Eigen-Filter Design for Ultrasound Flow Imaging Using a Multivariate Clustering
(University of Waterloo, 2020-01-23)Blood flow visualization is a challenging task in the presence of tissue motion. Unsuppressed tissue clutter produces flashing artefacts in ultrasound flow imaging which hampers blood flow detection by dominating part of ... -
Unsupervised learning for coherent structure identification in turbulent channel flow
(University of Waterloo, 2023-01-06)Coherent structures (CS), i.e., regions of flow exhibiting significant spatio-temporal coherence, have long been observed in turbulent fluid flow. These CS offer an opportunity to gain insights on fluid behaviour by bypassing ... -
Unsupervised Methods for Condition-Based Maintenance in Non-Stationary Operating Conditions
(University of Waterloo, 2022-04-28)Maintenance and operation of modern dynamic engineering systems requires the use of robust maintenance strategies that are reliable under uncertainty. One such strategy is condition-based maintenance (CBM), in which ...