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1.
Implementing Machine Learning Algorithms for Identifying Microstructure of Materials
by Shah, Niyati S., M.S.  California State University, Long Beach. 2018: 41 pages; 10837912.
3.
Structure Prediction and Variant Interpretation of Membrane Proteins Aided by Machine Learning Algorithms
by Li, Bian, Ph.D.  Vanderbilt University. 2018: 192 pages; 13917125.
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Self -taught learning
by Raina, Rajat, Ph.D.  Stanford University. 2009: 155 pages; 3382948.
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Learning Theory and Algorithms for Auctioning and Adaptation Problems
by Munoz Medina, Andres, Ph.D.  New York University. 2015: 260 pages; 3740907.
9.
Machine Learning in Neuroimaging
by Punugu, Venkatapavani Pallavi, M.S.  State University of New York at Buffalo. 2017: 41 pages; 10284048.
10.
Learning to Play Cooperative Games via Reinforcement Learning
by Wei, Ermo, Ph.D.  George Mason University. 2018: 162 pages; 13420351.
11.
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.
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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.
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.
15.
Machine learning for the automatic detection of anomalous events
by Fisher, Wendy D., Ph.D.  Colorado School of Mines. 2017: 173 pages; 10258193.
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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.
17.
In-Node Machine Learning-based Vehicle Classification
by Bhattarya, Rahul, M.S.  California State University, Long Beach. 2018: 62 pages; 10837826.
18.
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.
19.
Heterogeneous Treatment Effect Estimation Using Machine Learning
by Kuenzel, Soeren R., Ph.D.  University of California, Berkeley. 2019: 177 pages; 13903254.
20.
Machine Learning Methods for 3D Object Classification and Segmentation
by Le, Truc Duc, Ph.D.  University of Missouri - Columbia. 2018: 158 pages; 13877153.
21.
Counterfactual Evaluation and Learning From Logged User Feedback
by Swaminathan, Adith, Ph.D.  Cornell University. 2017: 224 pages; 10258968.
22.
An Approach to the Solution of Inverse Problem Using Unsupervised Machine Learning
by Dixit, Surabhi, M.S.  California State University, Long Beach. 2018: 64 pages; 10752219.
24.
Machine learning challenges for automated prompting in smart homes
by Das, Barnan, Ph.D.  Washington State University. 2014: 236 pages; 3640007.
25.
Positive-Unlabeled Learning in the Context of Protein Function Prediction
by Youngs, Noah, Ph.D.  New York University. 2014: 160 pages; 3665223.
26.
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.
27.
Practical Inference-Time Attacks against Machine-Learning Systems and a Defense against Them
by Sharif, Mahmood, Ph.D.  Carnegie Mellon University. 2019: 137 pages; 27662625.
28.
Task Relationship Modeling in Lifelong Multitask Learning
by Mishra, Meenakshi, Ph.D.  University of Kansas. 2015: 165 pages; 3721005.
29.
Cyber Incident Anomaly Detection Using Multivariate Analysis and Machine Learning
by Campbell, Ronald K., D.Engr.  The George Washington University. 2018: 121 pages; 10784357.
30.
Tactic-Based Learning for collective learning systems
by Armstrong, Alice, D.Sc.  The George Washington University. 2008: 320 pages; 3304083.
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