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1.
Kernel Based Relevance Vector Machine for Classification of Diseases
by Tcheimegni, Elie, D.Sc.  Bowie State University. 2013: 202 pages; 3558597.
2.
Learning to rank documents with support vector machines via active learning
by Arens, Robert James, Ph.D.  The University of Iowa. 2009: 113 pages; 3390239.
3.
Nonlinear epilepsy forewarning by support vector machines
by Ashbee, William S., M.S.  University of South Alabama. 2013: 51 pages; 1604736.
4.
Optimized Veterinary Thermographic Image Classification using Support Vector Machines and Noise Mitigation
by Lama, Norsang, M.S.  Southern Illinois University at Edwardsville. 2017: 56 pages; 10616467.
5.
Comparison of ad-hoc on demand distance vector and enhanced-ad-hoc on demand distance vector on vehicular ad-hoc networks
by Chandwasker, Tanmay, M.S.  California State University, Long Beach. 2016: 51 pages; 10011277.
6.
Computational methods for support vector machine classification and large-scale Kalman filtering
by Howard, Marylesa Marie, Ph.D.  University of Montana. 2013: 124 pages; 3568109.
7.
A Probabilistic Biomarker for Alzheimer's Disease
by Ayhan, Murat Seckin, Ph.D.  University of Louisiana at Lafayette. 2015: 103 pages; 10002384.
8.
The Structure of the Zebrafish Periderm Gene Regulatory Network and Its Relevance to Orofacial Clefting
by Duncan, Kaylia Mekelda, Ph.D.  The University of Iowa. 2019: 136 pages; 22588307.
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11.
Resolution Machines
by Sagwal, Himanshu, M.S.  California State University, Long Beach. 2019: 53 pages; 13857510.
12.
Analysis of genomic translation using a communications theory approach
by Al Bataineh, Mohammad, Ph.D.  Illinois Institute of Technology. 2010: 189 pages; 3435813.
13.
Decoupled Vector-Fetch Architecture with a Scalarizing Compiler
by Lee, Yunsup, Ph.D.  University of California, Berkeley. 2016: 157 pages; 10151006.
14.
Predicting Mental State Using Social Media Posts
by Seshadri, Subramaniam, M.S.  California State University, Long Beach. 2019: 56 pages; 13863615.
15.
Inference Algorithms and Sensorimotor Representations in Brains and Machines
by Mudigonda, Mayur, Ph.D.  University of California, Berkeley. 2019: 154 pages; 13904872.
16.
A new distributed framework for cyber attack detection and classification
by Gutta, Sandeep, M.S.  Oklahoma State University. 2011: 86 pages; 1506488.
17.
Approximating application performances in cloud data centers and simulated machines
by Islam, Mohammad Shahedul, Ph.D.  The University of Texas at San Antonio. 2016: 113 pages; 10249769.
19.
System for Identifying Plankton from the SIPPER Instrument Platform
by Kramer, Kurt A., Ph.D.  University of South Florida. 2010: 134 pages; 3432570.
20.
Molecular interactions between galectin-3 and prostate specific antigen: Relevance to prostate cancer
by Gilbride, Rebecca Jane, Ph.D.  University of Arkansas for Medical Sciences. 2012: 243 pages; 3551925.
21.
Database Streaming Compression on Memory-Limited Machines
by Bruccoleri, Damon, Ph.D.  Nova Southeastern University. 2018: 208 pages; 10751913.
23.
Automated Feature Engineering for Deep Neural Networks with Genetic Programming
by Heaton, Jeff, Ph.D.  Nova Southeastern University. 2017: 201 pages; 10259604.
25.
Algorithmic approaches to reducing resource costs in data centers
by Mukherjee, Koyel, Ph.D.  University of Maryland, College Park. 2013: 210 pages; 3612196.
27.
Relevance of meta information to scientific research
by Zehnder, Emanuel, D.M.  University of Phoenix. 2014: 193 pages; 3674144.
28.
The Persistence and Value-Relevance of Tax Expense
by Bell, Timothy Joseph, Ph.D.  University of Connecticut. 2012: 74 pages; 3533973.
29.
An ethnography of relevance in the digital age
by Bietila, David, M.A.  The George Washington University. 2010: 76 pages; 1480867.
30.
Image classification using invariant local features and contextual information
by Bharath, Ramesh, Ph.D.  National University of Singapore (Singapore). 2015: 178 pages; 10006074.
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