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242.
Selected Topics on Statistical Methods for Three and Multiple Class Diagnostic Studies
by Dong, Tuochuan, Ph.D.  State University of New York at Buffalo. 2014: 149 pages; 3629710.
243.
Black box methods for inferring parallel applications' properties in virtual environments
by Gupta, Ashish, Ph.D.  Northwestern University. 2008: 289 pages; 3303812.
244.
Communicating Plans in Ad Hoc Multiagent Teams
by Santarra, Trevor, Ph.D.  University of California, Santa Cruz. 2019: 190 pages; 13809871.
246.
Local spatial modeling using Geographically Weighted Regression (GWR)
by Wankie, Che, M.S.  California State University, Long Beach. 2013: 112 pages; 1523087.
247.
Methods in Computational Cosmology
by Vakili, Mohammadjavad, Ph.D.  New York University. 2017: 235 pages; 10260795.
248.
249.
Inferring differential rates of diversification from phylogenies
by Moore, Brian Ross, Ph.D.  Yale University. 2007: 685 pages; 3293407.
250.
Computational Mechanisms of Selective Attention During Reinforcement Learning
by Radulescu, Angela , Ph.D.  Princeton University. 2020: 133 pages; 27964412.
251.
Small Area Estimation in a Survey of Governments
by Dumbacher, Brian Arthur, Ph.D.  The George Washington University. 2016: 130 pages; 10075469.
252.
253.
Ancestry Informative Markers Tailored to Hispanic Populations
by Setser, Casandra Hernandez, Ph.D.  University of North Texas Health Science Center at Fort Worth. 2020: 97 pages; 27837053.
254.
Sample-specific cancer pathway analysis using PARADIGM
by Benz, Stephen C., Ph.D.  University of California, Santa Cruz. 2012: 124 pages; 3521746.
255.
Rate Types for Stream Programs
by Bartenstein, Thomas W., Ph.D.  State University of New York at Binghamton. 2017: 255 pages; 10643063.
256.
The complexity of flow analysis in higher-order languages
by Van Horn, David, Ph.D.  Brandeis University. 2009: 162 pages; 3369445.
257.
On information representation in the brain
by Tee, James Seng Khien, Ph.D.  New York University. 2017: 126 pages; 10188255.
258.
The ALISA Component Module: General shape classification for digital radiographic images
by Oertel, Carsten K., Ph.D.  The George Washington University. 2009: 276 pages; 3338836.
259.
On the Usability of Continuous Time Bayesian Networks: Improving Scalability and Expressiveness
by Perreault, Logan Jared, Ph.D.  Montana State University. 2017: 250 pages; 10258540.
260.
The Role of Data Geometry in Adversarial Machine Learning
by Bhagoji, Arjun Nitin, Ph.D.  Princeton University. 2020: 184 pages; 28095670.
261.
Stationary fields in object -oriented programs
by Unkel, Christopher, Ph.D.  Stanford University. 2009: 98 pages; 3395874.
262.
Test and Evaluation Resource Allocation Using Uncertainty Reduction as a Measure of Test Value
by Bjorkman, Eileen A., Ph.D.  The George Washington University. 2012: 349 pages; 3547993.
263.
Learning to Manipulate Novel Objects for Assistive Robots
by Sung, Jaeyong, Ph.D.  Cornell University. 2017: 190 pages; 10258261.
264.
Abstraction, Sense Distinctions and Syntax in Neural Semantic Role Labeling
by Gung, James, Ph.D.  University of Colorado at Boulder. 2020: 181 pages; 27838256.
265.
Learning to Learn with Gradients
by Finn, Chelsea B., Ph.D.  University of California, Berkeley. 2018: 199 pages; 10930398.
267.
Practical Backdoor Attacks and Defenses in Deep Learning Systems
by Yao, Yuanshun, Ph.D.  The University of Chicago. 2020: 181 pages; 28002642.
268.
Structural induction: Towards automatic ontology elicitation
by Silvescu, Adrian, Ph.D.  Iowa State University. 2008: 187 pages; 3307040.
269.
Accurate prediction of protein function using GOstruct
by Sokolov, Artem, Ph.D.  Colorado State University. 2011: 90 pages; 3489918.
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