This paper introduces a new class of quasi-Newton algorithms for unconstrained minimization in which no line search is necessary and the inverse Hessian approximations are positive definite. These ...

Entropy Minimization is a new clustering algorithm that works with both categorical and numeric data, and scales well to extremely large data sets. Data clustering is the process of placing data items ...

In this paper, we focus on solving convex minimization problem in the form of a summation of two convex functions in which one of them is Frecét differentiable. In order to solve this problem, we ...