By setting apart the two functions of a support vector machine: separation of points by a nonlinear surface in the original space of patterns, and maximizing the distance between separating planes in a higher dimensional ...

Genetic algorithms are one example of the use of a random element within an algorithm for combinatorial optimization. We consider the application of the genetic algorithm to a particular problem, the Assembly Line Balancing ...

Mixed complementarity problems can be recast as zero finding problems for the normal map, a function that is smooth on the interior o each of the cells of a piecewise linear manifold of IR^n, called normal manifold. We ...

A box constrained variational inequality problem can be reformulated as an unconstrained minimization problem through the D-gap function. A hybrid Netwon-type method is proposed for minimizing the D-gap function. Under ...

Theoretical and computational justification is given for improved generalization when the training set is learned with less accuracy. The model used for this investigation is a simple linear one. It is shown that learning ...

Several new interfaces have recently been developed requiring PATH to solve a mixed complementarity problem. To overcome the necessity of maintaining a different version of PATH for each interface, the code was reorganized ...

A finite new algorithm is proposed for clustering m given points in n-dimensional real space into k clusters by generating k planes that constitute a local solution to the nonconvex problem of minimizing the sum of squares ...

We are concerned with solving affine variational inequalities defined by a linear map A and a polyhedral set C. Most of the existing pivotal methods for such inequalities or mixed linear complementarity problems depend on ...

A linear support vector machine formulation is used to generate a fast, finitely-terminating linear-programming algorithm for discriminating between two massive sets in n-dimensional space, where the number of points can ...