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Skip to Search Results- 1Boers, Nicholas M.
- 1Foss, Andrew
- 1Moein Owhadi Kareshk
- 1Sidhu, Gagan
- 1Vlachaki, Aikaterini
- 1Wong, Alexander W.
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Spring 2021
The electrocardiogram is the standard tool for detecting cardiac abnormalities, such as atrial fibrillation, irregular complexes, and heart blocks. However, the interpretation of this data is an unsolved problem with discrepancies among panels of cardiologists and automated analysis requiring...
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Fall 2021
Deep neural network (DNN) has been developed rapidly in years. While it shows promising results in various tasks of computer vision, DNN typically suffers from accuracy loss due to the domain shift from a source domain to a target domain. To mitigate the accuracy loss without the label from...
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Spring 2020
During collaborative software development, developers often use branches to add features or fix bugs. When merging changes from two branches, conflicts may occur if the changes are inconsistent. Developers need to resolve these conflicts before completing the merge, which is an error-prone and...
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Toward Practical Reinforcement Learning Algorithms: Classification Based Policy Iteration and Model-Based Learning
DownloadSpring 2017
In this dissertation, we advance the theoretical understanding of two families of Reinforcement Learning (RL) methods: Classification-based policy iteration (CBPI) and model-based reinforcement learning (MBRL) with factored semi-linear models. In contrast to generalized policy iteration, CBPI...
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Synchronisation and Wavelet Compression for Background Interference Classification in Wireless Environments
DownloadFall 2017
Dense wireless deployment environments are increasingly facing Radio Frequency (RF) spectrum congestion and increased levels of interference. Addressing the interference will require a distributed decision-making application on wireless nodes, that characterize the state of the channel with...
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Fall 2012
Functional Magnetic Resonance Imaging (fMRI) measures the dynamic activity of each voxel of a brain. This dissertation addresses the challenge of learning a diagnostic classifier that uses a subject’s fMRI data to distinguish subjects with neuropsychiatric disorders from healthy controls. fMRI...
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Fall 2011
In this thesis, we focus on topics relevant to developing and deploying large-scale wireless sensor network (WSN) applications within real dynamic urban environments. Given few reported experiences in the literature, we designed our own such network to provide a foundation for our research. The...
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High-dimensional data mining: subspace clustering, outlier detection and applications to classification
DownloadSpring 2010
Data mining in high dimensionality almost inevitably faces the consequences of increasing sparsity and declining differentiation between points. This is problematic because we usually exploit these differences for approaches such as clustering and outlier detection. In addition, the exponentially...