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1.
Background and Occlusion Defenses Against Adversarial Examples and Adversarial Patches
by McCoyd, Michael J., Ph.D.  University of California, Berkeley. 2020: 75 pages; 28090541.
2.
Practical Inference-Time Attacks against Machine-Learning Systems and a Defense against Them
by Sharif, Mahmood, Ph.D.  Carnegie Mellon University. 2019: 137 pages; 27662625.
3.
The Role of Data Geometry in Adversarial Machine Learning
by Bhagoji, Arjun Nitin, Ph.D.  Princeton University. 2020: 184 pages; 28095670.
4.
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.
5.
Towards the Exploration and Improvement of Generative Adversarial Attacks
by Leone, Stephen, M.E.  The Cooper Union for the Advancement of Science and Art. 2020: 130 pages; 27994576.
6.
Learning to Play Cooperative Games via Reinforcement Learning
by Wei, Ermo, Ph.D.  George Mason University. 2018: 162 pages; 13420351.
9.
Unsupervised Learning under Uncertainty
by Mathieu, MichaĆ«l, Ph.D.  New York University. 2017: 159 pages; 10261120.
10.
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.
11.
Deep Learning Methods for Medical Image Computing
by Liao, Haofu, Ph.D.  University of Rochester. 2019: 237 pages; 27737049.
12.
Practical Backdoor Attacks and Defenses in Deep Learning Systems
by Yao, Yuanshun, Ph.D.  The University of Chicago. 2020: 181 pages; 28002642.
13.
DataVenom: A Genetic Algorithm Based Poisoning Attack Technique against Numeric Datasets
by Sloan, Joshua James, M.S.  University of Wyoming. 2020: 93 pages; 28257614.
14.
Model Based Clustering Algorithms with Applications
by Wei, Wutao, Ph.D.  Purdue University. 2018: 124 pages; 10830711.
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Artificial Neural Networks in Public Policy: Towards an Analytical Framework
by Lee, Joshua A., Ph.D.  George Mason University. 2020: 353 pages; 27956419.
18.
Interpretable Deep Learning for Natural Language Processing
by Murdoch, William James, Ph.D.  University of California, Berkeley. 2019: 114 pages; 13880811.
19.
Reinforcement Learning and Optimal Control in Complex Social Systems
by Yang, Fan, Ph.D.  State University of New York at Buffalo. 2020: 108 pages; 28087042.
20.
Analysis and Applications of the Locally Competitive Algorithm
by Paiton, Dylan M., Ph.D.  University of California, Berkeley. 2019: 99 pages; 13885693.
21.
Attention-Dependent and Continuous Representation Learning using Deep Autoencoders
by Dellana, Ryan, Ph.D.  North Carolina Agricultural and Technical State University. 2019: 104 pages; 22583727.
22.
Representation Learning on Sequential Medical Data
by Hyland, Stephanie L., Ph.D.  Weill Medical College of Cornell University. 2019: 245 pages; 13805668.
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Cyber Incident Anomaly Detection Using Multivariate Analysis and Machine Learning
by Campbell, Ronald K., D.Engr.  The George Washington University. 2018: 121 pages; 10784357.
25.
Visual Speech Perception of Arabic Emphatics and Gutturals
by Foster, Maha Saliba, Ph.D.  University of Colorado at Boulder. 2016: 170 pages; 10151052.
26.
Learning-Based Methods for Single Image Restoration and Translation
by Zhang, He, Ph.D.  Rutgers The State University of New Jersey, School of Graduate Studies. 2019: 149 pages; 10982777.
27.
Evaluation and Design of Robust Neural Network Defenses
by Carlini, Nicholas, Ph.D.  University of California, Berkeley. 2018: 138 pages; 10931076.
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Deep Learning for Digital Histopathology across Multiple Scales
by Hou, Le, Ph.D.  State University of New York at Stony Brook. 2019: 177 pages; 27670274.
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