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2.
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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Visual Speech Perception of Arabic Emphatics and Gutturals
by Foster, Maha Saliba, Ph.D.  University of Colorado at Boulder. 2016: 170 pages; 10151052.
6.
Towards Modeling Collaborative Task Oriented Multimodal Human-human Dialogues
by Chen, Lin, Ph.D.  University of Illinois at Chicago. 2014: 134 pages; 3668932.
7.
Scalable graph -based learning applied to human language technology
by Alexandrescu, Andrei, Ph.D.  University of Washington. 2009: 206 pages; 3377339.
8.
Algorithms for Interactive Machine Learning
by Poulis, Stefanos, Ph.D.  University of California, San Diego. 2019: 148 pages; 27542873.
9.
From Distribution Shift to Kernel Methods: A Study of Empirical Phenomena in Machine Learning
by Shankar, Vaishaal, Ph.D.  University of California, Berkeley. 2020: 203 pages; 28086200.
10.
Representation Learning for Text: Transfer Learning, Decomposition, and Bias in Neural Networks
by Romanov, Alexey, Ph.D.  University of Massachusetts Lowell. 2019: 103 pages; 22624438.
11.
Robust Classification of Emotion in Human Speech Using Spectrogram Features
by Guven, Erhan, Ph.D.  The George Washington University. 2012: 133 pages; 3502353.
12.
A study of the contribution of human factors to human-machine system failures in dynamic mission operations
by Davis, TImothy A., Ph.D.  The George Washington University. 2010: 189 pages; 3379259.
13.
A Machine Learning Approach to Genome Assessment
by Thrash, Charles Adam, Ph.D.  Mississippi State University. 2019: 104 pages; 22583353.
14.
Leveraging Deep Neural Networks to Study Human Cognition
by Peterson, Joshua C., Ph.D.  University of California, Berkeley. 2018: 129 pages; 10930700.
16.
Tactic-Based Learning for collective learning systems
by Armstrong, Alice, D.Sc.  The George Washington University. 2008: 320 pages; 3304083.
17.
Modernizing Check Fraud Detection with Machine Learning
by Rose, Lydia M., M.S.  Utica College. 2018: 64 pages; 13421455.
18.
Human Activity Analysis using Multi-modalities and Deep Learning
by Zhang, Chenyang, Ph.D.  The City College of New York. 2016: 115 pages; 10159927.
19.
Machine Learning and Biodata: Predicting Early Employee Flight During Preselection
by Bennett, Bryan P., D.B.A.  Capella University. 2020: 169 pages; 28090152.
21.
Ensemble supervised and unsupervised learning with Kepler variable stars
by Bass, Gideon, Ph.D.  George Mason University. 2015: 120 pages; 10027479.
22.
Learning from Temporally-Structured Human Activities Data
by Lipton, Zachary C., Ph.D.  University of California, San Diego. 2017: 274 pages; 10683703.
24.
Learning to Manipulate Novel Objects for Assistive Robots
by Sung, Jaeyong, Ph.D.  Cornell University. 2017: 190 pages; 10258261.
26.
Learning Neural Representations that Support Efficient Reinforcement Learning
by Stachenfeld, Kimberly, Ph.D.  Princeton University. 2018: 155 pages; 10824319.
29.
Combinatorial Neural Network Training Algorithm for Neuromorphic Computing
by Date, Prasanna, Ph.D.  Rensselaer Polytechnic Institute. 2019: 133 pages; 22583141.
30.
Background and Occlusion Defenses Against Adversarial Examples and Adversarial Patches
by McCoyd, Michael J., Ph.D.  University of California, Berkeley. 2020: 75 pages; 28090541.
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