We present a unified framework for reasoning about worst-case regret bounds for learning algorithms. This framework is based on the theory of duality of convex functions. It brin...
We consider the following network design problem. We are given an undirected network with costs on the edges, a set of terminals, and an upper bound for each terminal limiting the ...
Samuel Fiorini, Gianpaolo Oriolo, Laura Sanit&agra...
Abstract. The classic NFL theorems are invariably cast in terms of single objective optimization problems. We confirm that the classic NFL theorem holds for general multiobjective ...
This paper deals with the problem of comparing and testing evolutionary algorithms, that is, the benchmarking problem, from an analysis point of view. A practical study of the app...
We present a framework for solving multistage pure 0–1 programs for a widely used sequencing and scheduling problem with uncertainty in the objective function coefficients, the...
Antonio Alonso-Ayuso, Laureano F. Escudero, M. Ter...