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1.
Sparse dictionary learning and domain adaptation for face and action recognition
by Qiu, Qiang, Ph.D.  University of Maryland, College Park. 2013: 150 pages; 3587452.
2.
Sparse approximation and atomic decomposition: Considering atom interactions in evaluating and building signal representations
by Townsend Sturm, Bobby Lee, Jr., Ph.D.  University of California, Santa Barbara. 2009: 276 pages; 3350384.
3.
Texture Representations for Image Retrieval
by Shafer, Scott A., M.S.  The George Washington University. 2012: 65 pages; 1510228.
4.
Self -taught learning
by Raina, Rajat, Ph.D.  Stanford University. 2009: 155 pages; 3382948.
5.
Linking neural activity with perceptual decision making via sparse decoding
by Shi, Jianing, Ph.D.  Columbia University. 2010: 211 pages; 3428702.
6.
The Nonnegative Matrix Factorization: Methods and Applications
by Landi, Amanda Kim, Ph.D.  North Carolina State University. 2015: 120 pages; 10586642.
7.
Sparse and redundant representations for inverse problems and recognition
by Patel, Vishal M., Ph.D.  University of Maryland, College Park. 2010: 150 pages; 3426406.
8.
Visual tracking and illumination recovery via sparse representation
by Mei, Xue, Ph.D.  University of Maryland, College Park. 2009: 132 pages; 3391383.
9.
Spiking Neural Networks and Sparse Deep Learning
by Tavanaei, Amirhossein, Ph.D.  University of Louisiana at Lafayette. 2018: 176 pages; 10807940.
10.
Probabilistic models of phase variables for visual representation and neural dynamics
by Cadieu, Charles, Ph.D.  University of California, Berkeley. 2009: 120 pages; 3402686.
13.
The Performance of Random Prototypes in Hierarchical Models of Vision
by Stewart, Kendall Lee, M.S.  Portland State University. 2015: 79 pages; 1605894.
14.
Effective source separation algorithm using NMF and sparse NMF for acoustic fall detection
by Wang, Yanlin, M.S.  University of Missouri - Columbia. 2014: 119 pages; 10180882.
15.
Decoding of purely compressed-sensed video
by Liu, Ying, Ph.D.  State University of New York at Buffalo. 2012: 91 pages; 3541131.
16.
Sparse recovery and parameterization of manifold-valued data
by Taylor, Kye, M.S.  University of Colorado at Boulder. 2008: 105 pages; 1453576.
17.
Human Activity Analysis using Multi-modalities and Deep Learning
by Zhang, Chenyang, Ph.D.  The City College of New York. 2016: 115 pages; 10159927.
18.
Theoretical models of olfactory discrimination in Drosophila
by Luo, Sean Xiao, Ph.D.  Columbia University. 2009: 188 pages; 3393601.
19.
Learning Neural Representations that Support Efficient Reinforcement Learning
by Stachenfeld, Kimberly, Ph.D.  Princeton University. 2018: 155 pages; 10824319.
20.
Computational Methods for Dynamics and Mobility Analysis of Multiloop Mechanisms and Robotic Systems
by Wehage, Kristopher, Ph.D.  University of California, Davis. 2017: 277 pages; 10256858.
21.
Simulation of unsteady incompressible turbulent flows using Galerkin finite element and adaptive grids
by Ebeida, Mohamed S., Ph.D.  University of California, Davis. 2008: 145 pages; 3336416.
22.
Waveform-based velocity estimation from reflection seismic data
by Ma, Yong, Ph.D.  Colorado School of Mines. 2012: 166 pages; 3545176.
23.
Fast direct methods for molecular electrostatics
by Ho, Kenneth L., Ph.D.  New York University. 2012: 180 pages; 3524158.
24.
Optimization Methods Combining Variable Splitting with Deep Learning
by Cowen, Benjamin, Ph.D.  New York University Tandon School of Engineering. 2019: 136 pages; 13882605.
25.
Nonlocal and Randomized Methods in Sparse Signal and Image Processing
by Crandall, Robert, Ph.D.  The University of Arizona. 2018: 96 pages; 10840330.
26.
Attributed Object Maps: Descriptive Object Models as High-level Semantic Features for Mobile Robotics
by Delmerico, Jeffrey A., Ph.D.  State University of New York at Buffalo. 2013: 147 pages; 3598629.
27.
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.
28.
Multimodal biometrics – Representation, optimization and kernelization
by Avuthu, Poojita Reddy, M.S.  California State University, Long Beach. 2016: 44 pages; 10118895.
30.
Scalable Unsupervised Dense Objects Discovery, Detection, Tracking and Reconstruction
by Ma, Lu, Ph.D.  University of Colorado at Boulder. 2016: 160 pages; 10151087.
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