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1.
On Identification of Nonlinear Parameters in PDEs
by Kahler, Raphael, M.S.  Rochester Institute of Technology. 2016: 80 pages; 10117725.
2.
Inverse optimal control for deterministic continuous-time nonlinear systems
by Johnson, Miles J., Ph.D.  University of Illinois at Urbana-Champaign. 2013: 147 pages; 3632073.
3.
Waveform-based velocity estimation from reflection seismic data
by Ma, Yong, Ph.D.  Colorado School of Mines. 2012: 166 pages; 3545176.
5.
Sparse Regularization for Inverse Problems Governed by Evolution Equations
by Humber, Cary Ross, Ph.D.  North Carolina State University. 2011: 127 pages; 3463778.
6.
Applications of Convex Optimization Methods in Selected Transceiver Design Problems
by Jacklin, Neil Alexander, Ph.D.  University of California, Davis. 2013: 88 pages; 3596896.
7.
Optimization with multivariate stochastic dominance constraints
by Wolfhagen, Eli A., Ph.D.  Stevens Institute of Technology. 2015: 147 pages; 3715975.
8.
Solving Large-Scale Inverse Problems via Approximate Message Passing and Optimization
by Ma, Yanting, Ph.D.  North Carolina State University. 2017: 180 pages; 10758823.
9.
Radiation Source Mapping with Bayesian Inverse Methods
by Hykes, Joshua Michael, Ph.D.  North Carolina State University. 2012: 198 pages; 3538540.
10.
Simulation-based methods for stochastic control and global optimization
by Wang, Yongqiang, Ph.D.  University of Maryland, College Park. 2011: 195 pages; 3478991.
11.
Optimal wave focusing for seismic source imaging
by Bazargani, Farhad, Ph.D.  Colorado School of Mines. 2014: 150 pages; 3646086.
12.
Peephole superoptimization
by Bansal, Sorav, Ph.D.  Stanford University. 2008: 95 pages; 3332986.
13.
Modular Bayesian filters
by Edgington, Padraic D., Ph.D.  University of Louisiana at Lafayette. 2015: 366 pages; 3712276.
14.
High efficiency thrust vector control allocation
by Orr, Jeb S., Ph.D.  The University of Alabama in Huntsville. 2013: 91 pages; 3561548.
15.
Chaos, Observability and Symplectic Structure in Optimal Estimation
by Rey, Daniel, Ph.D.  University of California, San Diego. 2017: 185 pages; 10281245.
16.
Sparse and redundant representations for inverse problems and recognition
by Patel, Vishal M., Ph.D.  University of Maryland, College Park. 2010: 150 pages; 3426406.
17.
Solving two-level optimization problems with applications to robust design and energy markets
by Siddiqui, Sauleh Ahmad, Ph.D.  University of Maryland, College Park. 2011: 222 pages; 3495412.
18.
Using Simplified Models and Limited-Horizon Planning to React to Time-Critical Problems
by Lurz, Joshua Paul, D.Sc.  The George Washington University. 2019: 145 pages; 13419796.
19.
Multi-period natural gas market modeling Applications, stochastic extensions and solution approaches
by Egging, Rudolf Gerardus, Ph.D.  University of Maryland, College Park. 2010: 289 pages; 3443556.
20.
Mechatronics design process with energy optimization for industrial machines
by da Silva, Aderiano M., Ph.D.  Marquette University. 2015: 311 pages; 3701219.
21.
Real-Space Localization Methods for Minimizing the Kohn-Sham Energy
by Millstone, Marc, Ph.D.  New York University. 2011: 84 pages; 3466938.
22.
Topology optimization for wave propagation and vibration phenomena in elastic and piezoelectric solids
by Rupp, Cory J., Ph.D.  University of Colorado at Boulder. 2009: 213 pages; 3366657.
24.
Methodology for Tour-Based Truck Demand Modeling
by You, Soyoung Iris, Ph.D.  University of California, Irvine. 2012: 214 pages; 3502491.
26.
Inverse procedural modeling of trees
by Stava, Ondrej, Ph.D.  Purdue University. 2012: 124 pages; 10156257.
27.
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.
28.
A serial-parallel hybrid robot for machining of complex surfaces
by Shijun, Yan, Ph.D.  National University of Singapore (Singapore). 2015: 166 pages; 10006111.
29.
New neural network for real-time human dynamic motion prediction
by Bataineh, Mohammad Hindi, Ph.D.  The University of Iowa. 2015: 253 pages; 3711174.
30.
Large margin transformation learning
by Howard, Andrew G., Ph.D.  Columbia University. 2009: 90 pages; 3388470.
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