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dc.contributor.authorChen, Jieen_US
dc.date.accessioned2008-02-07T18:48:36Z
dc.date.available2008-02-07T18:48:36Z
dc.date.issued2007-11-01en_US
dc.identifier.urihttp://hdl.handle.net/1853/19841
dc.description.abstractTo overcome the curse of dimensionality, dimension reduction is important and necessary for understanding the underlying phenomena in a variety of fields. Dimension reduction is the transformation of high-dimensional data into a meaningful representation in the low-dimensional space. It can be further classified into feature selection and feature extraction. In this thesis, which is composed of four projects, the first two focus on feature selection, and the last two concentrate on feature extraction. The content of the thesis is as follows. The first project presents several efficient methods for the sparse representation of a multiple measurement vector (MMV); some theoretical properties of the algorithms are also discussed. The second project introduces the NP-hardness problem for penalized likelihood estimators, including penalized least squares estimators, penalized least absolute deviation regression and penalized support vector machines. The third project focuses on the application of manifold learning in the analysis and prediction of 24-hour electricity price curves. The last project proposes a new hessian regularized nonlinear time-series model for prediction in time series.en_US
dc.publisherGeorgia Institute of Technologyen_US
dc.subjectHRMen_US
dc.subjectTime series predictionen_US
dc.subjectElectricity price curveen_US
dc.subjectDimension reductionen_US
dc.subjectMMVen_US
dc.subjectPenalized likelihood estimatoren_US
dc.subject.lcshComputational complexity
dc.subject.lcshEstimation theory
dc.subject.lcshPrediction theory
dc.subject.lcshElectricity
dc.subject.lcshPricing
dc.titleTheoretical Results and Applications Related to Dimension Reductionen_US
dc.typeDissertationen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentIndustrial and Systems Engineeringen_US
dc.description.advisorCommittee Chair: Huo, Xiaoming; Committee Member: Deng, Shijie; Committee Member: Li, Minqiang; Committee Member: Serban, Nicoleta; Committee Member: Wu, Jeffen_US


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