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1.
Competing Factors in Phonological Learning Models: The Acquisition of English Consonant Clusters
by Reynolds, Amy R., M.A.  The University of North Carolina at Chapel Hill. 2011: 98 pages; 1500741.
2.
Simplifying algorithm learning using serious games
by Shabanah, Sahar Siraj, Ph.D.  George Mason University. 2010: 240 pages; 3407063.
3.
Task Relationship Modeling in Lifelong Multitask Learning
by Mishra, Meenakshi, Ph.D.  University of Kansas. 2015: 165 pages; 3721005.
4.
Self -taught learning
by Raina, Rajat, Ph.D.  Stanford University. 2009: 155 pages; 3382948.
5.
Positive-Unlabeled Learning in the Context of Protein Function Prediction
by Youngs, Noah, Ph.D.  New York University. 2014: 160 pages; 3665223.
6.
Neuroevolution Based Inverse Reinforcement Learning
by Budhraja, Karan Kumar, M.S.  University of Maryland, Baltimore County. 2016: 85 pages; 10140581.
7.
Semi-supervised learning for connectionist networks
by Robare, Rebecca J., Ph.D.  City University of New York. 2010: 117 pages; 3426834.
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9.
Learning to Play Cooperative Games via Reinforcement Learning
by Wei, Ermo, Ph.D.  George Mason University. 2018: 162 pages; 13420351.
10.
Interactive Learning for Sequential Decisions and Predictions
by Ross, Stephane, Ph.D.  Carnegie Mellon University. 2013: 294 pages; 3575525.
11.
Learning to Learn with Gradients
by Finn, Chelsea B., Ph.D.  University of California, Berkeley. 2018: 199 pages; 10930398.
12.
Learning Theory and Algorithms for Auctioning and Adaptation Problems
by Munoz Medina, Andres, Ph.D.  New York University. 2015: 260 pages; 3740907.
13.
A reinforcement learning model of gaze following
by Jasso, Hector, Ph.D.  University of California, San Diego. 2007: 130 pages; 3259369.
14.
Unsupervised linguistic inference
by Lamar, Michael T., Ph.D.  Brown University. 2010: 165 pages; 3430192.
15.
A game-theoretic comparison of genetic and model-based agents in learning strategic interactions
by Buntain, Cody, M.S.  The University of Alabama in Huntsville. 2010: 134 pages; 1484940.
16.
Large margin transformation learning
by Howard, Andrew G., Ph.D.  Columbia University. 2009: 90 pages; 3388470.
17.
A Study of Exploiting Objectness for Robust Online Object Tracking
by Yalamanchili, Raghu Kiran, M.S.  West Virginia University. 2013: 72 pages; 1524653.
18.
Creative Learning for Intelligent Robots
by Liao, Xiaoqun, Ph.D.  University of Cincinnati. 2006: 295 pages; 10857161.
19.
Scalable graph -based learning applied to human language technology
by Alexandrescu, Andrei, Ph.D.  University of Washington. 2009: 206 pages; 3377339.
20.
Discovery of Latent Factors in High-dimensional Data Using Tensor Methods
by Huang, Furong, Ph.D.  University of California, Irvine. 2016: 261 pages; 10125323.
21.
Semi-Supervised Learning for Electronic Phenotyping in Support of Precision Medicine
by Halpern, Yonatan, Ph.D.  New York University. 2016: 353 pages; 10192124.
22.
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.
23.
Spiking Neural Networks and Sparse Deep Learning
by Tavanaei, Amirhossein, Ph.D.  University of Louisiana at Lafayette. 2018: 176 pages; 10807940.
24.
Probabilistic learning for analysis of sensor-based human activity data
by Hutchins, Jonathan, Ph.D.  University of California, Irvine. 2010: 245 pages; 3432162.
25.
Inverse optimal control for deterministic continuous-time nonlinear systems
by Johnson, Miles J., Ph.D.  University of Illinois at Urbana-Champaign. 2013: 147 pages; 3632073.
26.
Advanced techniques for semantic concept detection in general videos
by Jiang, Wei, Ph.D.  Columbia University. 2010: 179 pages; 3420869.
27.
Counterfactual Evaluation and Learning From Logged User Feedback
by Swaminathan, Adith, Ph.D.  Cornell University. 2017: 224 pages; 10258968.
29.
Adaptive control and learning using multiple models
by Wang, Yu, Ph.D.  Yale University. 2017: 229 pages; 10783473.
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