Aiming at robust surface structure recovery, we extend the powerful optimization technique of variational shape approximation by allowing for several different primitives to repre...
Many of the recently proposed algorithms for learning feature-based ranking functions are based on the pairwise preference framework, in which instead of taking documents in isola...
Vitor R. Carvalho, Jonathan L. Elsas, William W. C...
We present a new method, called UTAGMS , for multiple criteria ranking of alternatives from set A using a set of additive value functions which result from an ordinal regression. ...
Salvatore Greco, Vincent Mousseau, Roman Slowinski
Variance is a classical measure of a point estimator's sampling error. In steady-state simulation experiments, many estimators of this variance--or its square root, the stand...
This paper deals with ranking and selection problem via simulation. We present an optimal computing budget allocation technique which can select the best of k simulated designs. T...