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1.
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.
2.
Development of Geodetic Imaging Techniques and Machine Learning for Marsh Observation
by Nguyen, Chuyen, Ph.D.  Texas A&M University - Corpus Christi. 2019: 205 pages; 13859552.
3.
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.
4.
Classifying Websites Using Word Vectors and Other Techniques: An Application of Zipf’s Law
by Robles, Alejandro, M.S.  California State University, Long Beach. 2019: 50 pages; 22589849.
5.
Machine learning for the automatic detection of anomalous events
by Fisher, Wendy D., Ph.D.  Colorado School of Mines. 2017: 173 pages; 10258193.
6.
Machine Learning in Neuroimaging
by Punugu, Venkatapavani Pallavi, M.S.  State University of New York at Buffalo. 2017: 41 pages; 10284048.
7.
Latent Variable Modeling for Networks and Text: Algorithms, Models and Evaluation Techniques
by Foulds, James Richard, Ph.D.  University of California, Irvine. 2014: 287 pages; 3631094.
8.
Machine learning challenges for automated prompting in smart homes
by Das, Barnan, Ph.D.  Washington State University. 2014: 236 pages; 3640007.
9.
An investigation of data privacy and utility using machine learning as a gauge
by Mivule, Kato, D.Sc.  Bowie State University. 2014: 262 pages; 3619387.
10.
Modernizing Check Fraud Detection with Machine Learning
by Rose, Lydia M., M.S.  Utica College. 2018: 64 pages; 13421455.
11.
Cyber Incident Anomaly Detection Using Multivariate Analysis and Machine Learning
by Campbell, Ronald K., D.Engr.  The George Washington University. 2018: 121 pages; 10784357.
12.
Advanced techniques for semantic concept detection in general videos
by Jiang, Wei, Ph.D.  Columbia University. 2010: 179 pages; 3420869.
13.
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.
14.
Predicting National Basketball Association Game Outcomes Using Ensemble Learning Techniques
by Valenzuela, Russell, M.S.  California State University, Long Beach. 2018: 54 pages; 10980443.
15.
Implementing Machine Learning Algorithms for Identifying Microstructure of Materials
by Shah, Niyati S., M.S.  California State University, Long Beach. 2018: 41 pages; 10837912.
16.
Tactic-Based Learning for collective learning systems
by Armstrong, Alice, D.Sc.  The George Washington University. 2008: 320 pages; 3304083.
17.
Supervised and Unsupervised Learning for Semantics Distillation in Multimedia Processing
by Liu, Yu, Ph.D.  State University of New York at Buffalo. 2018: 150 pages; 10932367.
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19.
Novel Function Approximation Techniques for Large-scale Reinforcement Learning
by Wu, Cheng, Ph.D.  Northeastern University. 2010: 130 pages; 3443846.
20.
Structure Prediction and Variant Interpretation of Membrane Proteins Aided by Machine Learning Algorithms
by Li, Bian, Ph.D.  Vanderbilt University. 2018: 192 pages; 13917125.
21.
Machine-Learning Methods for Credit Card Fraud Detection
by Woolston, Sarah E., M.S.  California State University, Long Beach. 2017: 100 pages; 10602012.
22.
Driver drowsiness detection using ECG integrated with machine learning
by Solanki, Khantil N., M.S.  California State University, Long Beach. 2017: 84 pages; 10263492.
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.
Learning to Play Cooperative Games via Reinforcement Learning
by Wei, Ermo, Ph.D.  George Mason University. 2018: 162 pages; 13420351.
25.
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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27.
Counterfactual Evaluation and Learning From Logged User Feedback
by Swaminathan, Adith, Ph.D.  Cornell University. 2017: 224 pages; 10258968.
28.
Analytical techniques for the improvement of mass spectrometry protein profiling
by Pelikan, Richard Craig, Ph.D.  University of Pittsburgh. 2011: 251 pages; 3472018.
29.
Atomistic Monte Carlo Simulation and Machine Learning Data Analysis of Eutectic Alkali Metal Alloys
by Reitz, Doug, Ph.D.  George Mason University. 2018: 118 pages; 10982615.
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