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CSCI 2950E - Stochastic Optimization |
This advanced graduate course/seminar will focus on optimization under uncertainty, or optimization problems where some of the constrains include random (stochastic) components. Most practical optimization problems are stochastic (subject to future market conditions, weather, faults, etc.), and there has been substantial research (both theoretical and experimental) in efficient solution for such problems. We'll read and discuss some of the recent works in this area.
0.000 OR 1.000 Credit hours 0.000 OR 1.000 Lecture hours Levels: Graduate, Undergraduate Schedule Types: Discussion Section/Conference, Primary Meeting Computer Science Department |
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