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1.
Communication and estimation in noisy networks
by Vedantam, Satish, Ph.D.  University of Southern California. 2009: 168 pages; 3355383.
2.
Multiple targets detection and tracking with Doppler effect in noisy acoustic wireless sensor networks
by An, Youngwon Kim, Ph.D.  The University of Alabama in Huntsville. 2013: 167 pages; 3558526.
3.
Collective Relational Data Integration with Diverse and Noisy Evidence
by Memory, Alexander, Ph.D.  University of Maryland, College Park. 2019: 204 pages; 27547597.
4.
Noise, Quantization, and Priors in Neural Networks
by Anderson, Alexander G., Ph.D.  University of California, Berkeley. 2018: 87 pages; 10822107.
5.
Autonomous Localization in 3D Surface Wireless Sensor Networks
by Zhao, Yao, Ph.D.  University of Louisiana at Lafayette. 2014: 45 pages; 3622968.
6.
Social networks within policy networks: The case of Maine's Climate Change Action Plan
by Morris, Teague Beaux, Ph.D.  University of Southern Maine. 2010: 161 pages; 3422286.
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Authority Flow-based Ranking in Heterogeneous Networks: Prediction, Personalization, and Learning to Rank
by Sayyadi-Harikandehei, Hassan, Ph.D.  University of Maryland, College Park. 2014: 107 pages; 3628017.
12.
Topology in sensor networks
by Skraba, Primoz, Ph.D.  Stanford University. 2008: 133 pages; 3343959.
13.
Robust hough transform for noisy and cluttered images
by Slininger, Timothy, M.S.  Southern Connecticut State University. 2014: 197 pages; 1525183.
14.
Topics in MIMO networks
by Tajer, Seyed Ali, Ph.D.  Columbia University. 2010: 166 pages; 3447999.
15.
Spiking Neural Networks and Sparse Deep Learning
by Tavanaei, Amirhossein, Ph.D.  University of Louisiana at Lafayette. 2018: 176 pages; 10807940.
17.
Dynamics and Information Processing in Recurrent Networks
by Kuczala, Alexander, Ph.D.  University of California, San Diego. 2019: 112 pages; 27541198.
18.
Scalable and Efficient Tasking for Dynamic Sensor Networks
by Dang, Thanh Xuan, Ph.D.  Portland State University. 2011: 135 pages; 3468959.
19.
Electroencephalogram classification by forecasting with recurrent neural networks
by Forney, Elliott M., M.S.  Colorado State University. 2011: 79 pages; 1503664.
20.
Wireless Communication Systems Modeling and Design Using Communication Theory
by Allehaibi, Saleh Saeed S., Ph.D.  The University of Alabama at Birmingham. 2018: 171 pages; 10978201.
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Semi-Supervised Learning for Electronic Phenotyping in Support of Precision Medicine
by Halpern, Yonatan, Ph.D.  New York University. 2016: 353 pages; 10192124.
23.
Distributed estimation over networks with communication costs
by Lipsa, Gabriel-Mihai, Ph.D.  University of Maryland, College Park. 2010: 188 pages; 3426416.
24.
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.
26.
Towards spatial queries over phenomena in sensor networks
by Jin, Guang, Ph.D.  The University of Maine. 2009: 202 pages; 3364695.
27.
Nonlocal and Randomized Methods in Sparse Signal and Image Processing
by Crandall, Robert, Ph.D.  The University of Arizona. 2018: 96 pages; 10840330.
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Towards Temporal Semantic Scene Understanding
by Ghafarianzadeh, Mahsa, Ph.D.  University of Colorado at Boulder. 2017: 152 pages; 10271366.
30.
Complex-Valued Deep Learning With Applications to Magnetic Resonance Image Synthesis
by Virtue, Patrick M., Ph.D.  University of California, Berkeley. 2019: 153 pages; 22619704.
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