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by
Green, Michael A., author.
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the research literature. My work focuses on ROI detection tuned to subtle differences for images at
by
Chen, Jie, author.
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prediction of squared financial returns is defined and analyzed in Chapter 2. Our work on linear time series
by
Gao, Christian Siyao, author.
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fast, scalable, performs well, and will work on any classification problem as long as the training data
by
Woytarowicz, Nicole, author.
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(variables) of a network with unknown structure, much work has been done in recent years to recover the
by
Du, Chengan, author.
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, using both network topology and nodal covariates. In the first part of our work (Chapter 2), we
by
Ma, Chong, author.
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using FDR in the large scale testing problem. One work proposes a novel algorithm to yield reproducible
by
Nguyen, Son, author.
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vectors in the linear combinations of the covariate vector X. In this work, we propose a new method to
by
Ng, Carmen Doris, author.
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. But as these countries continue to work on problems of under-nutrition, over-nutrition has been rising
by
Haber, Gregory W., author.
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underlying parameter so that previous work has relied heavily on large sample methods to establish results
by
Semedo, Joao D., author.
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flexible, changing rapidly under different stimulus contexts. This work thus provides a foundation for
by
Demirdjian, Levon, author.
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-seq datasets continue to pose significant data analysis challenges to researchers. In this work, we propose new
by
Xie, Meihui, author.
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work is motivated by the need for generative models to understand the mechanisms behind the observed
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