Abstract. We study two-stage, finite-scenario stochastic versions of several combinatorial optimization problems, and provide nearly tight approximation algorithms for them. Our pr...
We study the approximability and inapproximability of finding identifying codes and locating-dominating codes of the minimum size. In general graphs, we show that it is possible ...
This paper is devoted to the analysis of network approximation in the framework of approximation and regularization theory. It is shown that training neural networks and similar n...
We study the approximability of the maximum solution problem. This problem is an optimisation variant of the constraint satisfaction problem and it captures a wide range of interes...
Hyperbolic cross approximations by some classical orthogonal polynomials/functions in both bounded and unbounded domains are considered in this paper. Optimal error estimates in pr...