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1.
Applications of k-means and spectral clustering to hyperspectral video sequences
by Sunu, Justin, M.S.  California State University, Long Beach. 2014: 72 pages; 1526959.
3.
Weighted clustering ensembles
by Al-Razgan, Muna Saleh, Ph.D.  George Mason University. 2008: 146 pages; 3323309.
4.
Spectral Analysis of Directed Graphs using Matrix Perturbation Theory
by Li, Yuemeng, Ph.D.  The University of North Carolina at Charlotte. 2017: 143 pages; 10618933.
6.
Clustering datasets with singular value decomposition
by Douglas, Emmeline P., M.S.  College of Charleston. 2008: 85 pages; 1461189.
7.
Exploiting spatial and spectral information in hyperdimensional imagery
by Lee, Matthew Allen, Ph.D.  Mississippi State University. 2012: 104 pages; 3522207.
9.
Application of Graph Theoretic Clustering on Some Biomedical Data Sets
by Ahlert, Darla, M.S.  Southern Illinois University at Edwardsville. 2015: 59 pages; 1588658.
11.
Statistical methods for high-dimensional data analysis
by Gupta, Abhishek, Ph.D.  University of Pennsylvania. 2008: 96 pages; 3346226.
13.
14.
Clustering transient data streams by example and by variable
by Chaovalit, Pimwadee, Ph.D.  University of Maryland, Baltimore County. 2009: 224 pages; 3359104.
15.
The K(n)-local E n-Adams Spectral Sequence and a Cohomological Approximation of its E2-term
by Petrovic, Vojislav, Ph.D.  University of Louisiana at Lafayette. 2017: 88 pages; 10623147.
16.
Clustering algorithms for next-generation sequencing data from heterogenous populations
by Prabhakara, Shruthi, Ph.D.  The Pennsylvania State University. 2012: 126 pages; 3737327.
17.
Speech Segregation in Background Noise and Competing Speech
by Hu, Ke, Ph.D.  The Ohio State University. 2012: 147 pages; 10631003.
18.
Stochastic Data Clustering
by Wessell, Charles David, Ph.D.  North Carolina State University. 2011: 102 pages; 3479609.
19.
Modeling alternatives to solve the connected graph k-clustering problem
by Es-Sakli, Nada, M.S.  Lehigh University. 2011: 74 pages; 1488515.
20.
Detecting Phenology Markers for Discernment of Grass Species at High Spatial and Temporal Scales
by Pakalniskis, Alexander Anthony, M.A.  California State University, Long Beach. 2019: 39 pages; 13425958.
21.
Lasers and landing sites: The geomorphology, stratigraphy, and composition of Mars
by Anderson, Ryan, Ph.D.  Cornell University. 2012: 262 pages; 3501197.
22.
Higher-order Random Walk Methods for Data Analysis
by Wu, Tao, Ph.D.  Purdue University. 2018: 135 pages; 10790747.
23.
Analysis of environmental sounds
by Lee, Keansub, Ph.D.  Columbia University. 2009: 116 pages; 3388467.
24.
Machine learning for the automatic detection of anomalous events
by Fisher, Wendy D., Ph.D.  Colorado School of Mines. 2017: 173 pages; 10258193.
25.
Towards Temporal Semantic Scene Understanding
by Ghafarianzadeh, Mahsa, Ph.D.  University of Colorado at Boulder. 2017: 152 pages; 10271366.
26.
Approximation of Positive Semidefinite Matrices Using the Nyström Method
by Arcolano, Nicholas Francis, Ph.D.  Harvard University. 2011: 247 pages; 3462777.
27.
Understanding activity from trajectory patterns
by Morris, Brendan Tran, Ph.D.  University of California, San Diego. 2010: 146 pages; 3398750.
28.
Assessing the Robustness of Clustering Methods for use in Vegetation Classification
by Dell, Noah David, M.S.  Southern Illinois University at Edwardsville. 2017: 108 pages; 10275943.
29.
Image analysis for realistic electromagnetic imaging systems
by Ramirez-Velez, Mabel Delice, Ph.D.  University of Colorado at Boulder. 2009: 172 pages; 3366658.
30.
Improving non-linear approaches to anomaly detection, class separation, and visualization
by Paciencia, Todd J., Ph.D.  Air Force Institute of Technology. 2014: 354 pages; 3667806.
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