KERNEL-FUNCTION BASED ALGORITHMSFOR SEMIDEFINITE OPTIMIZATION

Recently, Y.Q. Bai, M. El Ghami and C. Roos [3 ]intro-duced a new class of so-called eligible kernel functions which are definedby some simple conditions. The authors designed primal-dual interior-point methods for linear optimization (LO) based on eligible kernelfunctions and simplified the analysis of these methods considerably.In this paper we consider the semidefinite optimization (SDO) prob-lem and we generalize the aforementioned results for LO to SDO. Theiteration bo unds obtained are analogous to the results in [ 3]forLO