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1.
Tactic-Based Learning for collective learning systems
by Armstrong, Alice, D.Sc.  The George Washington University. 2008: 320 pages; 3304083.
2.
Visual Speech Perception of Arabic Emphatics and Gutturals
by Foster, Maha Saliba, Ph.D.  University of Colorado at Boulder. 2016: 170 pages; 10151052.
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Optimizing Machine Translation by Learning to Search
by Galron, Daniel, Ph.D.  New York University. 2012: 218 pages; 3546405.
5.
Machine Learning in Neuroimaging
by Punugu, Venkatapavani Pallavi, M.S.  State University of New York at Buffalo. 2017: 41 pages; 10284048.
6.
The Human Learning Machine: Rational Constructivist Models of Conceptual Development
by Mollica, Francis, Ph.D.  University of Rochester. 2019: 222 pages; 22589492.
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Machine-Learning Methods for Credit Card Fraud Detection
by Woolston, Sarah E., M.S.  California State University, Long Beach. 2017: 100 pages; 10602012.
8.
Learning Neural Representations that Support Efficient Reinforcement Learning
by Stachenfeld, Kimberly, Ph.D.  Princeton University. 2018: 155 pages; 10824319.
9.
A Machine Learning Approach to Genome Assessment
by Thrash, Charles Adam, Ph.D.  Mississippi State University. 2019: 104 pages; 22583353.
10.
In-Node Machine Learning-based Vehicle Classification
by Bhattarya, Rahul, M.S.  California State University, Long Beach. 2018: 62 pages; 10837826.
11.
Using Machine Learning Methods to Predict NFL Victors
by Urista Benitez, Octavio Misael, M.S.  California State University, Long Beach. 2017: 88 pages; 10606129.
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Learning to Play Cooperative Games via Reinforcement Learning
by Wei, Ermo, Ph.D.  George Mason University. 2018: 162 pages; 13420351.
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Modernizing Check Fraud Detection with Machine Learning
by Rose, Lydia M., M.S.  Utica College. 2018: 64 pages; 13421455.
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Vehicle classification using machine learning algorithm
by Patel, Darshan D., M.S.  California State University, Long Beach. 2015: 37 pages; 1604876.
15.
Machine Learning Applications to Robot Control
by Abdul-hadi, Omar, Ph.D.  University of California, Berkeley. 2018: 93 pages; 10817183.
16.
Heterogeneous Treatment Effect Estimation Using Machine Learning
by Kuenzel, Soeren R., Ph.D.  University of California, Berkeley. 2019: 177 pages; 13903254.
17.
Self -taught learning
by Raina, Rajat, Ph.D.  Stanford University. 2009: 155 pages; 3382948.
18.
Implementing Machine Learning Algorithms for Identifying Microstructure of Materials
by Shah, Niyati S., M.S.  California State University, Long Beach. 2018: 41 pages; 10837912.
19.
Machine Learning and Cellular Automata: Applications in Modeling Dynamic Change in Urban Environments
by Curtis, Brian J., D.Engr.  The George Washington University. 2018: 84 pages; 10785215.
20.
Decision tree-based machine learning algorithm for in-node vehicle classification
by Trivedi, Ankit P., M.S.  California State University, Long Beach. 2016: 66 pages; 10196455.
21.
Enhanced Machine Learning Engine Engineering Using Innovative Blending, Tuning, and Feature Optimization
by Uddin, Muhammad Fahim, Ph.D.  University of Bridgeport. 2018: 192 pages; 13427950.
22.
Machine Learning and Network-Based Systems Toxicology Modeling of Chemotherapy-Induced Peripheral Neuropathy
by Bloomingdale, Peter, Ph.D.  State University of New York at Buffalo. 2018: 353 pages; 13427432.
23.
A Machine Learning Approach to Quantifying Likely Locations of Gas and Gas Hydrate Accumulation
by Runyan, Taylor E., M.S.  University of Louisiana at Lafayette. 2017: 55 pages; 10268964.
24.
Machine Learning for the Automated Identification of Cyberbullying and Cyberharassment
by Ducharme, Daniel N., Ph.D.  University of Rhode Island. 2017: 145 pages; 10259474.
25.
Machine Learning Methods for 3D Object Classification and Segmentation
by Le, Truc Duc, Ph.D.  University of Missouri - Columbia. 2018: 158 pages; 13877153.
26.
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.
27.
Machine learning challenges for automated prompting in smart homes
by Das, Barnan, Ph.D.  Washington State University. 2014: 236 pages; 3640007.
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Classification of Placental Chorionic Surface Vasculature Network Features Using Machine Learning Techniques
by Hambarsoomian, Hike, M.S.  California State University, Long Beach. 2017: 50 pages; 10603969.
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