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32735 open access dissertations and theses found for:
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1.
Statistical Methods for High Dimensional Variable Selection
by Li, Kaiqiao, Ph.D.  State University of New York at Stony Brook. 2019: 114 pages; 13427291.
2.
Associations and Confounding in High-Dimensional Genomics
by Darnell, Gregory Byer, Ph.D.  Princeton University. 2019: 169 pages; 13865166.
3.
Statistical methods for high-dimensional data analysis
by Gupta, Abhishek, Ph.D.  University of Pennsylvania. 2008: 96 pages; 3346226.
4.
Weighted voting ensembles for high dimensional data
by Hordoan, Liliana A., M.S.  California State University, Long Beach. 2015: 67 pages; 1584935.
5.
Controlling for hidden factors in high dimensional eQTL studies
by Gao, Chuan, Ph.D.  Cornell University. 2012: 106 pages; 3520145.
6.
Robust and efficient feature selection for high-dimensional datasets
by Mo, Dengyao, Ph.D.  University of Cincinnati. 2011: 131 pages; 3458192.
7.
Statistical models and optimization algorithms for high-dimensional computer vision problems
by Mitra, Kaushik, Ph.D.  University of Maryland, College Park. 2011: 155 pages; 3478970.
9.
Some Statistical Methods on Design, Modeling and Analysis of High-Dimensional Data
by Shang, Shulian, Ph.D.  New York University. 2012: 120 pages; 3524267.
10.
Spatial relationships in high-dimensional, international, and historical data
by Knippenberg, Ross William, Ph.D.  University of Colorado at Boulder. 2014: 130 pages; 3621355.
12.
Roughened Random Forests for Binary Classification
by Xiong, Kuangnan, Ph.D.  State University of New York at Albany. 2014: 136 pages; 3624962.
13.
Human-Data Interaction in Large and High-Dimensional Data
by Amraii, Saman Amirpour, Ph.D.  University of Pittsburgh. 2017: 192 pages; 10831835.
14.
Discovery of Latent Factors in High-dimensional Data Using Tensor Methods
by Huang, Furong, Ph.D.  University of California, Irvine. 2016: 261 pages; 10125323.
15.
Systemic Networks for High-Dimensional Exposures and Health Outcomes
by Lee, Jai Woo, Ph.D.  Dartmouth College. 2019: 92 pages; 13885205.
16.
Efficient Markov Chain Monte Carlo Methods
by Fang, Youhan, Ph.D.  Purdue University. 2018: 107 pages; 10809188.
18.
Factor models: Testing and forecasting
by Yao, Jiawei, Ph.D.  Princeton University. 2015: 114 pages; 3682786.
21.
Making statistics matter: Self-data as a possible means to improve statistics learning
by Thayne, Jeffrey L., Ph.D.  Utah State University. 2016: 276 pages; 10250713.
23.
Learning functions on unknown manifolds
by Zhou, Xueyuan, Ph.D.  The University of Chicago. 2011: 126 pages; 3487652.
24.
Exploring and Sampling on High Dimensional Free Energy Surfaces
by Chen, Ming, Ph.D.  New York University. 2016: 183 pages; 10025680.
25.
26.
Tree-Based Ensemble Classification Algorithms for Genomic Data
by Doan, Quoc A., M.S.  California State University, Long Beach. 2020: 54 pages; 27736947.
27.
A Clinical Decision Support System for the Prevention of Genetic-Related Heart Disease
by Saguilig, Lauren G., M.S.  California State University, Long Beach. 2017: 42 pages; 10264716.
29.
Noise, Quantization, and Priors in Neural Networks
by Anderson, Alexander G., Ph.D.  University of California, Berkeley. 2018: 87 pages; 10822107.
30.
Weighted Distance Weighted Discrimination and pairwise variable selection for classification
by Qiao, Xingye, Ph.D.  The University of North Carolina at Chapel Hill. 2010: 136 pages; 3418734.
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