Ph.D Theses

 

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Ph.D Theses

Author: Sarikaya, Alper T (The University of Wisconsin – Madison)  2017,  Advisor: Gleicher, Michael L. 

Perreault, Logan Jared. (Montana State University) “On the Usability of Continuous Time Bayesian Networks: Improving Scalability and Expressiveness” (2017), Advisor: Sheppard, John W., https://www.cs.montana.edu/sheppard/

Igor Moáco Guerreiro, Federal University of Ceará, Brazil (2017), "Distributed optimization techniques for 4G and beyond", advisor: Charles Casimiro Cavalcante

Pourkamali Anaraki, Farhad. University of Colorado at Boulder,(2017) "Randomized Algorithms for Large-Scale Data Analysis", advisor: Becker, Stephen

Massive high-dimensional data sets are ubiquitous in all scientific disciplines.

Fan, Bin. Michigan State University, (2017) "Polycrystalline diamond based neural interface for optogenetics and neurotransmitter detection" advisor: Wen Li

Zhu, Zhenghan. University of Rhode Island (2017)"Some Contributions to Radar Detection Theory", advisor: Kay, Steven

Kaewtip, Kantapon. University of California, Los Angeles(2017)"Robust Automatic Recognition of Birdsongs and Human Speech: a Template-Based Approach", advisor: Alwan, Abeer

Hossein Bashashati, University of British Columbia (2017) "A User-Customized Self-Paced Brain Computer Interface", advisor: Gary Birch

Much attention has been directed towards synchronous Brain Computer Interfaces (BCIs). For these BCIs, the user can only operate the system during specific system-defined periods. Self-paced BCIs, however, allow users to operate the system at any time he/she wishes. The classification of Electroencephalography (EEG) signals in self-paced BCIs is extremely challenging.

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