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1.
Minimum Disparity Inference for Discrete Ranked Set Sampling Data
by Alexandridis, Roxana, Ph.D.  The Ohio State University. 2005: 137 pages; 10834940.
2.
Robust Inference and Group Sequential Methods in Discrete Hazard Models
by Nguyen, Vinh Quang, Ph.D.  University of California, Irvine. 2011: 204 pages; 3477976.
4.
Advances in Weak Identification and Robust Inference for Generically Identified Models
by Cox, Gregory Fletcher, Ph.D.  Yale University. 2017: 306 pages; 10633240.
5.
Robust network inference with multivariate t-distributions
by Finegold, Michael A., Ph.D.  The University of Chicago. 2010: 94 pages; 3419771.
6.
Robust and efficient inference of scene and object motion in multi-camera systems
by Sankaranarayanan, Aswin C., Ph.D.  University of Maryland, College Park. 2009: 181 pages; 3391385.
7.
Deep Learning for Attribute Inference, Parsing, and Recognition of Face
by Luo, Ping, Ph.D.  The Chinese University of Hong Kong (Hong Kong). 2014: 122 pages; 3691916.
9.
Performance analysis and inference of communication networks
by Ni, Jian, Ph.D.  Yale University. 2008: 178 pages; 3342752.
10.
Robust Inference and Network Analysis for Non-Gaussian Gene-Expression Data
by Specht, Alicia T., Ph.D.  University of Notre Dame. 2017: 126 pages; 13836379.
11.
Optimal Subset Selection for Causal Inference Using Machine Learning and Particle Swarm Optimization
by Sharma, Dhruv, D.Engr.  The George Washington University. 2018: 132 pages; 10928545.
12.
Phylogenomic Analysis of Fundulidae Using RNA-Sequencing Data
by Rodgers, Rachel, M.S.  Southern Illinois University at Edwardsville. 2017: 72 pages; 10265232.
13.
Collaborative Targeted Maximum Likelihood Estimation
by Gruber, Susan, Ph.D.  University of California, Berkeley. 2011: 160 pages; 3499349.
14.
Interactive Learning for Sequential Decisions and Predictions
by Ross, Stephane, Ph.D.  Carnegie Mellon University. 2013: 294 pages; 3575525.
16.
Methodology for Fleet Uncertainty Reduction with Unsupervised Learning
by Modarres, Ceena, M.S.  University of Maryland, College Park. 2016: 77 pages; 10253325.
18.
Reconstructing the evolutionary history of RNA viruses using relaxed molecular clocks
by Wertheim, Joel Okrent, Ph.D.  The University of Arizona. 2009: 146 pages; 3378827.
19.
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.
20.
Analysis and Applications of the Locally Competitive Algorithm
by Paiton, Dylan M., Ph.D.  University of California, Berkeley. 2019: 99 pages; 13885693.
21.
Hierarchical Bayes estimation and empirical best prediction of small-area proportions
by Liu, Benmei, Ph.D.  University of Maryland, College Park. 2009: 223 pages; 3359401.
22.
Inferring tumor evolution using computational phylogenetics
by Subramanian, Ayshwarya, Ph.D.  Carnegie Mellon University. 2013: 132 pages; 3575067.
23.
Nonparametric Bayes: Inference under nonignorable missingness and model selection
by Linero, Antonio, Ph.D.  University of Florida. 2015: 147 pages; 10299009.
24.
Bayesian Nonparametric Methods for Analysis of Electronic Health Records
by Xu, Dandan, Ph.D.  University of Florida. 2016: 108 pages; 10679207.
26.
Information theoretic approaches towards regulatory network inference
by Chaitankar, VIjender, Ph.D.  Virginia Commonwealth University. 2012: 125 pages; 3550865.
27.
Semi-Supervised Learning for Electronic Phenotyping in Support of Precision Medicine
by Halpern, Yonatan, Ph.D.  New York University. 2016: 353 pages; 10192124.
28.
Essays on Causal Inference in Randomized Experiments
by Lin, Winston, Ph.D.  University of California, Berkeley. 2013: 93 pages; 3593906.
29.
Robust Estimation of Parametric Models for Insurance Loss Data
by Poudyal, Chudamani, Ph.D.  The University of Wisconsin - Milwaukee. 2018: 127 pages; 10829498.
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