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1.
Weighted clustering ensembles
by Al-Razgan, Muna Saleh, Ph.D.  George Mason University. 2008: 146 pages; 3323309.
2.
Probabilistic Clustering Ensemble Evaluation for Intrusion Detection
by McElwee, Steven M., Ph.D.  Nova Southeastern University. 2018: 166 pages; 10844875.
3.
Development of Geodetic Imaging Techniques and Machine Learning for Marsh Observation
by Nguyen, Chuyen, Ph.D.  Texas A&M University - Corpus Christi. 2019: 205 pages; 13859552.
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A case study on the importance and value of the Desert Winds steelpan programs
by Haskett, Brandon Lee, D.M.A.  Arizona State University. 2009: 227 pages; 3361302.
7.
Clustering transient data streams by example and by variable
by Chaovalit, Pimwadee, Ph.D.  University of Maryland, Baltimore County. 2009: 224 pages; 3359104.
8.
Modeling alternatives to solve the connected graph k-clustering problem
by Es-Sakli, Nada, M.S.  Lehigh University. 2011: 74 pages; 1488515.
9.
Dissimilarity and Optimal Sampling in Urn Ensembles
by Hampton, Jerrad, Ph.D.  University of Colorado at Boulder. 2012: 123 pages; 3527293.
10.
Weighted voting ensembles for high dimensional data
by Hordoan, Liliana A., M.S.  California State University, Long Beach. 2015: 67 pages; 1584935.
11.
Stochastic Data Clustering
by Wessell, Charles David, Ph.D.  North Carolina State University. 2011: 102 pages; 3479609.
12.
Senior adult music learning, motivation, and meaning construction in two New Horizons ensembles
by Tsugawa, Samuel, D.M.A.  Arizona State University. 2009: 224 pages; 3392131.
13.
Rock music performance ensembles in New Jersey secondary education
by Stroh, Edward D., M.M.  The William Paterson University of New Jersey. 2013: 187 pages; 1548559.
14.
Botnet Detection Using Graph Based Feature Clustering
by Akula, Ravi Kiran, M.S.  Mississippi State University. 2018: 69 pages; 10751733.
15.
Small Jazz Ensembles and Ideals of Urban Social Interaction
by Chen, Kaori Otera, M.A.  State University of New York at Albany. 2016: 70 pages; 10110405.
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Studies of spatial clustering of inertial particles in turbulence
by Saw, Ewe Wei, Ph.D.  Michigan Technological University. 2008: 164 pages; 3339459.
18.
Network structures: Graph theory, statistics, and neuroscience applications
by Chang, Yu-Teng, Ph.D.  University of Southern California. 2012: 146 pages; 3513735.
19.
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.
23.
Clustering datasets with singular value decomposition
by Douglas, Emmeline P., M.S.  College of Charleston. 2008: 85 pages; 1461189.
24.
Spatially coupled LDPC codes and cooperative communication
by Wei, Lai, Ph.D.  University of Notre Dame. 2015: 166 pages; 3731723.
26.
Clustering and entity resolution for semi-structured data
by Zhao, Chuan, Ph.D.  Washington State University. 2011: 208 pages; 3495962.
27.
Mean Field Theory for Protein Side-chain Prediction: Improvements and Applications
by Francis-Lyon, Patricia A., Ph.D.  University of California, Davis. 2011: 146 pages; 3482127.
29.
An Investigation of Anomaly-based Ensemble Models for Multi-domain Intrusion Detection
by Mikhail, Joseph W., D.Engr.  The George Washington University. 2019: 117 pages; 10977908.
30.
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.
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