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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.
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4.
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.
5.
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.
6.
The Role of Data Geometry in Adversarial Machine Learning
by Bhagoji, Arjun Nitin, Ph.D.  Princeton University. 2020: 184 pages; 28095670.
7.
Analysis and Applications of the Locally Competitive Algorithm
by Paiton, Dylan M., Ph.D.  University of California, Berkeley. 2019: 99 pages; 13885693.
8.
Computer Aided Analysis of Prostate Histopathology Images
by Ren, Jian, Ph.D.  Rutgers The State University of New Jersey, School of Graduate Studies. 2019: 142 pages; 22623293.
9.
Model Based Clustering Algorithms with Applications
by Wei, Wutao, Ph.D.  Purdue University. 2018: 124 pages; 10830711.
10.
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.
11.
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.
14.
Practical Backdoor Attacks and Defenses in Deep Learning Systems
by Yao, Yuanshun, Ph.D.  The University of Chicago. 2020: 181 pages; 28002642.
15.
Unsupervised Learning under Uncertainty
by Mathieu, MichaĆ«l, Ph.D.  New York University. 2017: 159 pages; 10261120.
16.
Log-Periodic Microstrip Patch Antenna Miniaturization Using Artificial Magnetic Conductor Surfaces
by Almutawa, Ahmad T., M.S.E.E.  University of South Florida. 2011: 69 pages; 1496395.
18.
Towards Interpretable Models of Health
by Hallgrimsson, Harldur Tomas, Ph.D.  University of California, Santa Barbara. 2020: 123 pages; 28095664.
20.
Evaluation and Design of Robust Neural Network Defenses
by Carlini, Nicholas, Ph.D.  University of California, Berkeley. 2018: 138 pages; 10931076.
21.
Protecting Smart Devices from the Bottom-Up
by Machiry, Aravind K., Ph.D.  University of California, Santa Barbara. 2020: 179 pages; 28092431.
23.
Interpretable Deep Learning for Natural Language Processing
by Murdoch, William James, Ph.D.  University of California, Berkeley. 2019: 114 pages; 13880811.
24.
Secure Distributed Inference
by Chen, Yuan, Ph.D.  Carnegie Mellon University. 2019: 169 pages; 13883829.
25.
Margin of Error
by Jackson-Weaver, Van, M.F.A.  Mills College. 2020: 29 pages; 27994955.
26.
Weakly Supervised Visual Understanding
by Zou, Yang, Ph.D.  Carnegie Mellon University. 2020: 170 pages; 28095257.
27.
Deep Learning Methods for Medical Image Computing
by Liao, Haofu, Ph.D.  University of Rochester. 2019: 237 pages; 27737049.
28.
DataVenom: A Genetic Algorithm Based Poisoning Attack Technique against Numeric Datasets
by Sloan, Joshua James, M.S.  University of Wyoming. 2020: 93 pages; 28257614.
29.
Exploring the Effects of Frontalization and Data Synthesis on Face Recognition
by Banerjee, Sandipan, Ph.D.  University of Notre Dame. 2019: 189 pages; 27750532.
30.
Learning to Play Cooperative Games via Reinforcement Learning
by Wei, Ermo, Ph.D.  George Mason University. 2018: 162 pages; 13420351.
1 - 30 of 5205 displayed.
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