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1.
Real-Time Adaptive Data-Driven Perception for Anomaly Priority Scoring at Scale
by Miraftabzadeh, Seyed Ali, Ph.D.  The University of Texas at San Antonio. 2017: 142 pages; 10686275.
2.
Self -taught learning
by Raina, Rajat, Ph.D.  Stanford University. 2009: 155 pages; 3382948.
3.
Counterfactual Evaluation and Learning From Logged User Feedback
by Swaminathan, Adith, Ph.D.  Cornell University. 2017: 224 pages; 10258968.
4.
Relationship within principal leadership behavior, organizational health, and academic achievement of at-risk students
by Chauvin, Shelly Dufresne, Ed.D.  Southeastern Louisiana University. 2010: 128 pages; 3482191.
6.
Learning to Learn with Gradients
by Finn, Chelsea B., Ph.D.  University of California, Berkeley. 2018: 199 pages; 10930398.
7.
Task Relationship Modeling in Lifelong Multitask Learning
by Mishra, Meenakshi, Ph.D.  University of Kansas. 2015: 165 pages; 3721005.
8.
Advanced techniques for semantic concept detection in general videos
by Jiang, Wei, Ph.D.  Columbia University. 2010: 179 pages; 3420869.
9.
Learning Neural Representations that Support Efficient Reinforcement Learning
by Stachenfeld, Kimberly, Ph.D.  Princeton University. 2018: 155 pages; 10824319.
10.
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.
11.
Text Representation using Convolutional Networks
by Zhang, Xiang, Ph.D.  New York University. 2019: 164 pages; 10928487.
12.
User inspired management of scientific jobs in grids and clouds
by Withana, Eran Chinthaka, Ph.D.  Indiana University. 2011: 151 pages; 3488334.
13.
Improving Biological Object Classification in Plankton Images Using Convolutional Neural Networks, Geometric Features, and Context Metadata
by Ellen, Jeffrey Scott, Ph.D.  University of California, San Diego. 2018: 233 pages; 10933313.
14.
A Comparison of Variance and Renyi's Entropy with Application to Machine Learning
by Peccarelli, Adric M., M.S.  Northern Illinois University. 2017: 38 pages; 10603911.
16.
Perspective-based learning in virtual environments
by Lindgren, Robb, Ph.D.  Stanford University. 2009: 155 pages; 3364505.
17.
Belief based reinforcement learning for data fusion
by Lollett, Carlos, Ph.D.  State University of New York at Buffalo. 2009: 184 pages; 3342148.
18.
Unsupervised Learning under Uncertainty
by Mathieu, Michaël, Ph.D.  New York University. 2017: 159 pages; 10261120.
20.
Computational methods for support vector machine classification and large-scale Kalman filtering
by Howard, Marylesa Marie, Ph.D.  University of Montana. 2013: 124 pages; 3568109.
21.
Large margin transformation learning
by Howard, Andrew G., Ph.D.  Columbia University. 2009: 90 pages; 3388470.
22.
Re-conceptualizing the organizing circumstance of learning
by Spear Ellinwood, Karen Courtenay, Ph.D.  The University of Arizona. 2011: 288 pages; 3464975.
23.
Learning to Play Cooperative Games via Reinforcement Learning
by Wei, Ermo, Ph.D.  George Mason University. 2018: 162 pages; 13420351.
24.
Positive-Unlabeled Learning in the Context of Protein Function Prediction
by Youngs, Noah, Ph.D.  New York University. 2014: 160 pages; 3665223.
25.
Interactive Learning for Sequential Decisions and Predictions
by Ross, Stephane, Ph.D.  Carnegie Mellon University. 2013: 294 pages; 3575525.
27.
Deep Learning Robust Perception Paradigm for Autonomous Vehicles
by Ali, Alaa Mohamed Leithy, Ph.D.  University of Louisiana at Lafayette. 2017: 134 pages; 10681320.
28.
Personally satisfying: Using personal style scales to enhance the prediction of career satisfaction
by Hees, Charles K., Ph.D.  Southern Illinois University at Carbondale. 2010: 237 pages; 3426712.
29.
Novel Function Approximation Techniques for Large-scale Reinforcement Learning
by Wu, Cheng, Ph.D.  Northeastern University. 2010: 130 pages; 3443846.
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