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1.
Counterfactual Evaluation and Learning From Logged User Feedback
by Swaminathan, Adith, Ph.D.  Cornell University. 2017: 224 pages; 10258968.
2.
Self -taught learning
by Raina, Rajat, Ph.D.  Stanford University. 2009: 155 pages; 3382948.
3.
Task Relationship Modeling in Lifelong Multitask Learning
by Mishra, Meenakshi, Ph.D.  University of Kansas. 2015: 165 pages; 3721005.
4.
Learning to Play Cooperative Games via Reinforcement Learning
by Wei, Ermo, Ph.D.  George Mason University. 2018: 162 pages; 13420351.
6.
Learning to Learn with Gradients
by Finn, Chelsea B., Ph.D.  University of California, Berkeley. 2018: 199 pages; 10930398.
7.
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.
8.
Lower Bound Resource Requirements for Machine Intelligence
by Gilmanov, Timur, Ph.D.  Indiana University. 2018: 149 pages; 10980279.
9.
Interactive Learning for Sequential Decisions and Predictions
by Ross, Stephane, Ph.D.  Carnegie Mellon University. 2013: 294 pages; 3575525.
10.
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.
11.
The Human Learning Machine: Rational Constructivist Models of Conceptual Development
by Mollica, Francis, Ph.D.  University of Rochester. 2019: 222 pages; 22589492.
12.
Learning Ambidexterity in Organization
by Zabiegalski, Eric, Ed.D.  The George Washington University. 2015: 177 pages; 3715905.
13.
Belief based reinforcement learning for data fusion
by Lollett, Carlos, Ph.D.  State University of New York at Buffalo. 2009: 184 pages; 3342148.
14.
Large margin transformation learning
by Howard, Andrew G., Ph.D.  Columbia University. 2009: 90 pages; 3388470.
15.
Positive-Unlabeled Learning in the Context of Protein Function Prediction
by Youngs, Noah, Ph.D.  New York University. 2014: 160 pages; 3665223.
16.
Scalable graph -based learning applied to human language technology
by Alexandrescu, Andrei, Ph.D.  University of Washington. 2009: 206 pages; 3377339.
18.
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.
19.
Deep Learning for Information Extraction
by Nguyen, Thien Huu, Ph.D.  New York University. 2018: 246 pages; 10260911.
20.
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.
21.
Multi-tier Internet service management: Statistical learning approaches
by Muppala, Sireesha, Ph.D.  University of Colorado at Colorado Springs. 2013: 167 pages; 3560749.
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23.
Modernizing Check Fraud Detection with Machine Learning
by Rose, Lydia M., M.S.  Utica College. 2018: 64 pages; 13421455.
24.
Creative Learning for Intelligent Robots
by Liao, Xiaoqun, Ph.D.  University of Cincinnati. 2006: 295 pages; 10857161.
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.
Automatic Snooker-Playing Robot with Speech Recognition Using Deep Learning
by Bhagat, Kunj H., M.S.  California State University, Long Beach. 2018: 61 pages; 10977867.
28.
Tactic-Based Learning for collective learning systems
by Armstrong, Alice, D.Sc.  The George Washington University. 2008: 320 pages; 3304083.
29.
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.
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