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by
Zhu, Huanhuan, author.
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, I did this power comparison work. The results show that none of the methods is consistently more
by
Berchuck, Samuel L., author.
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In chapter 2, we work within the framework of boundary detection and introduce a spatiotemporal
by
Barkley, Brian G., author.
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the outcome of another individual. This work aims to develop statistical methodology for inference
by
Moon, Jessie Eunyoung, author.
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analysis is not appropriate. In this thesis, we extend von Luxburg's work to 3-dimensional spatially
by
Wong, Sze Wai, author.
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main objective of the first part of this work is to show that, like the Euclidean space, the affine
by
Shirman, Aleksandra, author.
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work are used to validate common assumptions in machine learning work such as the dependence of the
by
Zhao, Zifeng, author.
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Throughout my Ph.D. life, I mainly work on research topics about time series. This thesis consists
by
Yao, Xuan, author.
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integrated functions of times at risk and others. Inspired by Tsiatis's work in 1990, by defining martingale
by
Hellams, Luvenia Nicole, author.
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kurtosis of the original data, while better conserving the type-I error rate of the test. This work
by
Skripnikov, Andrey, author.
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In this work we develop various frameworks for performing joint regularized estimation of multiple
by
Yin, Tianzhixi, author.
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methodologies to PMU data from October 2016 to May 2017. This work involves training machine learning algorithms
by
Ananth, Varsha, author.
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. For future work there are several directions to expand the problem scope. One such approach would be

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