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Development of Partially Supervised Kernel-based Proximity Clustering Frameworks and Their Applications
DownloadSpring 2011
The focus of this study is the development and evaluation of a new partially supervised learning framework. This framework belongs to an emerging field in machine learning that augments unsupervised learning processes with some elements of supervision. It is based on proximity fuzzy clustering,...
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Spring 2013
Many machine learning algorithms learn from the data by capturing certain interesting characteristics. Decision trees are used in many classification tasks. In some circumstances, we only want to consider fixed-depth trees. Unfortunately, finding the optimal depth-d decision tree can require time...
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Fall 2015
This dissertation first introduces the concepts of robust active learning (also called optimal experimental design in statistics), and the possible advantages of it over the traditional passive learning method. Then a general regression problem with possibly misspecified models is presented, and...
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Robust Probabilistic Principal Component Analysis Based Modeling with Gaussian Mixture Noises
DownloadFall 2021
Most of the industrial plants are heavily instrumented with a large number of sensors and analyzers to provide the data needed for process control and monitoring purposes. However, online and fast-rate measurements are not always available due to restricted availability and/or reliability of...
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Spring 2015
Image texture is defined as visual patterns appearing in images. The powerful perceptive capability of texture features has made texture analysis a major research topic in computer vision and image processing. Texture features are used to detect defective products in factories, to understand...
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Fall 2014
In this thesis, time-varying behaviour, nonlinearity and switching dynamics are generally treated as multi-modal behaviour. Two multi-model modelling techniques, i.e., the linear parameter varying (LPV) technique and the switched modelling technique, are investigated to model the multi-modal...