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- 13D structure prediction
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Fall 2021
Kernel methods are often used for nonlinear regression and classification in machine learning because they are computationally cheap and accurate. Fourier basis and wavelet basis are the bases that can efficiently approximate the kernel functions. In previous research, Bayesian approximate kernel...
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Fall 2009
The analysis of wide-angle cellular light scattering patterns is a challenging problem. Small changes to the organization, orientation, shape, and optical properties of scatterers and scattering populations can significantly alter their complex two-dimensional scattering signatures. Because of...
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Fall 2017
This thesis focuses on formulating and analyzing non linear models for microbial dynamics vis-a-vis human and environmental health. Firstly, we develop and investigate a stoichiometric organic matter decomposition model in a chemostat culture that incorporates the dynamics of grazers. This...
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Fall 2020
In distributed computing models, where some helper nodes assist the master in a large-scale computation, a big challenge is when these helpers straggle. The straggling of even a single helper node can significantly increase the processing time. Therefore, coded distributed computing has been...