Abstract: Optimization problems lie at the core of scientific and engineering endeavors. Solutions to these problems are often compute-intensive. To fulfill their compute-resource requirements, ...

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Since its creation more than two decades ago by Daniel Spielman (above) and Shang-hua Teng, smoothed analysis has been used to analyze performance of algorithms other than the simplex method, ...

Linear programming is the most fundamental optimization problem with applications in many areas including engineering, management, and economics. The simplex method is a practical and efficient ...

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ABSTRACT: The computation of the basis inverse is the most time-consuming step in simplex type algorithms. This inverse does not have to be computed from scratch at any iteration, but updating schemes ...

The paper presents an approach for avoiding and minimizing the complementary pivots in a simplex based solution method for a quadratic programming problem. The linearization of the problem is slightly ...

Abstract: Existing active set methods reported in the literature for support vector machine (SVM) training must contend with singularities when solving for the search direction. When a singularity is ...

"Please enter the coefficients in matrix c:15000 14000 15000 14000 15000 14000 1000 1000 1000 1000 1000 1000 -20000 -17000 -20000 -17000 -20000 -17000 0 0 0 0 0 0 0 0 ...