Efficient numerical algorithms for regularized regression problem with applications to traffic matrix estimations

Understand

In this work we collect and compare to each other many different numerical methods for regularized regression problem and for the problem of projection on a hyperplane.

• Such problems arise, for example, as a subproblem of demand matrix estimation in IP- networks.
• In this special case matrix of affine constraints has special structure: all elements are 0 or 1 and this matrix is sparse enough.
• We have to deal with huge-scale convex optimization problem of special type.