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Browsing by Author "Dozier, Gerry"
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Improving Prediction Accuracy Using Class-specific Ensemble Feature Selection
Soares, Caio (2010-08-03)
As data accumulates at a speed significantly faster than can be processed, data preprocessing techniques such as feature selection become increasingly important and beneficial. Moreover, given the well-known gains of ...
Investigation of EtherYatri’s Compatibility with IPV6
Nemani, Srinivasa (2006-08-15)
Internet Protocol version six (IPv6) enjoys only a scant existence today. Many universities, companies and other organizations are building protocol stacks, hardware and applications to support IPv6, awaiting its full-fledged ...
A Meta-Parallel Evolutionary System for Solving Optimization Problems
Britt, Winard (2007-05-15)
The purpose of the Meta-Parallel Evolutionary System (MPES) is to develop fast,
efficient parallel evolutionary systems for function optimization. Given an optimization
problem and a set number of nodes available for the ...
Neural Enhancement for Multiobjective Optimization
Garrett, Aaron (2008-05-15)
In this work, a neural network approach is applied to multiobjective optimization problems in order to expand the set of optimal solutions. The network is trained using results obtained from existing evolutionary multiobjective ...
Novel Approaches for Cancer Subtypes Discovery and Pathway Analysis
Bya, Phi Hung (2024-04-15) ETD File Embargoed
Complex diseases, particularly cancer, encompass a wide range of disorders, from ag- gressive and lethal to indolent lesions with low or delayed potential for progression to death. Treatment options and success heavily ...
Post-Speech-Recognition Processing in Domain-Specific Text-Corpus-Based Distributed Listening System: Analysis, Interpretation and Selection of Speech Recognition Results
Lee, Spencer (2006-12-15)
Achieving usable recognition rates has been an almost never-ending quest in speech recognition research for more than three decades. Recently speech recognition rates have dramatically improved in conjunction with the rapid ...
A Study of Adversarial Attacks on Machine Learning-based Fake News Detection Systems
Brown, Brandon (2023-05-04) ETD File Embargoed
Due to the increased use and reliance on social media, fake news has become a significant problem that can cause great harm to individuals. Because of the dangerousness of fake news, techniques must be developed to detect ...
Towards understanding computer vision system
Peijie, Chen (2024-05-03)
In the realm of machine learning and deep neural networks, despite the significant strides made across diverse applications, the understanding and interpretation of these models, particularly under adversarial conditions ...