Graduate Computer Science
Graduate Computer Science
2017 Spring Term
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3
Units
OPTIMIZATION: TECHNIQUES AND APPLICATIONS
COMPSCI 735
The course takes a unified view of optimization, covering the main areas of application and the main optimization algorithms. The topics include linear optimization, robust optimization, network flows, discrete optimization, dynamic optimization and nonlinear optimization. The course involves learning about, using, and analyzing the results of state of the art optimization software.
3
Units
BIG DATA AND DATA MINING
COMPSCI 767
This course will cover two main areas: (1) machine learning algorithms that can be applied to "big data" (i.e., data sets of great size and complexity); and (2) distributed file systems and MapReduce as tools to generate algorithms, along with associated hardware innovations to facilitate parallel analysis of big data.