In this paper we consider a new analytic center cutting plane method in a projective space. We prove the efficiency for the general scheme and show that these results can be used in the analysis of a feasability problem, the variational inequality problem and the problem if constrained...

In this paper we consider a homogeneous analytic center cutting plabne method in a projective space. We describe a general scheme that uses a homogeneous oracle and computes an approximate analytic center at each iteration. This technique is applied to a convex feasibility problem, to...

In this paper we study special barrier functions for the convex cones, which are the sum of a self-concordant barrier for the cone and a positive-semidefinite quadratric form. We show that the central path of these augmented barrier functions can be traced with linear speed. We also study the...

We propose an alternative apporach to stochastic programming based on Monte-Carlo sampling and stochastic gradient optimization. The procedure is by essence probabilistic and the computed solution is a random variable. The associated objectiev value is doubly random, since it depends two...