Abstract
NUOPT is an optimization software developed by Mathematical Systems Inc. It has many kinds of algorithms, and also has a nice modeling language named SIMPLE. Recently, a primal-dual interior point method for semidefinite programming has been developed and implemented into NUOPT. In the optimization field, Semidefinite Programming Problems have been studied intensively nowadays. They belong to the class of convex optimization problems and therefore can be solved quickly by sophisticated interior point methods. This paper introduce NUOPT and its applications of Semidefinite Programming in statistical analysis. For example, machine learning (semidefinite logit model and semidefinite support vector machine), nearest correlation matrix problem (matrix completion problem), and optimal designs. There are several results solved by NUOPT.
