A derivation of so-called “soft-margin Support Vector Machines with kernel” is presented which does not rely on concepts from functional analysis such as Mercer’s theorem that is frequently cited in this context, and that leads to a new analysis of the continuity properties of the kernel functions such as a new self-concordance condition for the … Read more
In a real Hilbert space V, the conic hull of G is the set cone(G) consisting of all nonnegative linear combinations of elements of G. Many optimization problems are sensitive to the changes in cone(G) that result from changes in G itself. Motivated by one such problem, we derive necessary and sufficient conditions for the … Read more
In this paper, we study several classes of set-valued maps, which can be used in set-valued optimization and its applications, and their respective maximum and minimum value functions. The definitions of these maps are based on scalar-valued, vector-valued, and cone-valued maps. Moreover, we consider those extremal value functions which are obtained when optimizing linear functionals … Read more