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2.
Spiking Neural Networks and Sparse Deep Learning
by Tavanaei, Amirhossein, Ph.D.  University of Louisiana at Lafayette. 2018: 176 pages; 10807940.
3.
Application of temporal difference learning to the game of Snake
by Lockhart, Christopher, M.Eng.  University of Louisville. 2010: 96 pages; 1485160.
4.
An evolutionary method for training autoencoders for deep learning networks
by Lander, Sean, M.S.  University of Missouri - Columbia. 2014: 43 pages; 10180878.
5.
Attention to Deep Structure in Recurrent Neural Networks
by Sharpe, Spencer S., M.S.  University of Wyoming. 2017: 62 pages; 10619110.
6.
Automated Feature Engineering for Deep Neural Networks with Genetic Programming
by Heaton, Jeff, Ph.D.  Nova Southeastern University. 2017: 201 pages; 10259604.
7.
Creative Learning for Intelligent Robots
by Liao, Xiaoqun, Ph.D.  University of Cincinnati. 2006: 295 pages; 10857161.
8.
Electroencephalogram classification by forecasting with recurrent neural networks
by Forney, Elliott M., M.S.  Colorado State University. 2011: 79 pages; 1503664.
9.
Blood Glucose Management Streptozotocin-Induced Diabetic Rats by Artificial Neural Network Based Model Predictive Control
by Bahremand, Saeid, M.S.  Southern Illinois University at Edwardsville. 2016: 92 pages; 10249804.
10.
The Supporting Role of Walk-Throughs in the Value-Added Assessment Era: Perceptions from School Administrators
by Moore, Louis Lamar, D.E.  University of Louisiana at Lafayette. 2019: 251 pages; 13427119.
11.
Integrating Multiple Modalities into Deep Learning Networks
by McNeil, Patrick N., Ph.D.  Nova Southeastern University. 2017: 296 pages; 10283417.
12.
Semi-supervised learning for connectionist networks
by Robare, Rebecca J., Ph.D.  City University of New York. 2010: 117 pages; 3426834.
13.
Learning-Assisted Market-Based Optimization for Truck Task Scheduling
by Danna, Russell J., M.S.  University of Louisiana at Lafayette. 2014: 56 pages; 1557547.
14.
Learning from Temporally-Structured Human Activities Data
by Lipton, Zachary C., Ph.D.  University of California, San Diego. 2017: 274 pages; 10683703.
15.
Optimization Methods Combining Variable Splitting with Deep Learning
by Cowen, Benjamin, Ph.D.  New York University Tandon School of Engineering. 2019: 136 pages; 13882605.
16.
Geometric representations and deep Gaussian conditional random field networks for computer vision
by Vemulapalli, Raviteja, Ph.D.  University of Maryland, College Park. 2016: 185 pages; 10192530.
18.
Deep Networks for Forward Prediction and Planning
by Henaff, Mikael, Ph.D.  New York University. 2018: 164 pages; 10928805.
19.
Comparison and Fine-Grained Analysis of Sequence Encoders for Natural Language Processing
by Keller, Thomas Anderson, M.S.  University of California, San Diego. 2017: 87 pages; 10599339.
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Utilizing Various Neural Network Architectures to Play a Game Developed for Human Players
by Arender, Blake, M.S.  The University of Mississippi. 2018: 51 pages; 10752390.
22.
Extinction with a concurrent excitor in Pavlovian fear conditioning
by Witnauer, James, Ph.D.  State University of New York at Binghamton. 2010: 128 pages; 3419176.
23.
Transitioning through gender, transitioning through life
by Magee, Patric Andrew, M.S.W.  California State University, Long Beach. 2010: 87 pages; 1486501.
25.
Being through books: A phenomenological study of constructing a sense of self through fiction
by McShane, Laura Marie, Ph.D.  University of Maryland, College Park. 2010: 285 pages; 3443484.
26.
Through the eyes of a child: A symbolic, narrative journey through complex childhood trauma
by Fernandez, Bonnie Rose, M.A.  Pacifica Graduate Institute. 2010: 117 pages; 1490015.
28.
Modeling the mirror system in action observation and execution
by Bonaiuto, James, Ph.D.  University of Southern California. 2010: 291 pages; 3418250.
29.
Classification of prevention through drama cyber-bullying programs in Nassau County
by Lenz, Valerie Robin, M.F.A.  State University of New York at Stony Brook. 2012: 50 pages; 1529628.
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