An important theoretical tool in machine learning is the bias/variance decomposition of the generalization error. It was introduced for the mean square error in [3]. The bias/vari...
We present a new propagator achieving bound consistency for the INTER-DISTANCE constraint. This constraint ensures that, among a set of variables X1, . . . , Xn, the difference be...
Probabilistic inference techniques can be used to estimate variable bias, or the proportion of solutions to a given SAT problem that fix a variable positively or negatively. Metho...
— Network operators control the flow of traffic through their networks by adapting the configuration of the underlying routing protocols. For example, they tune the integer li...
Finite-domain constraint programming has been used with great success to tackle a wide variety of combinatorial problems in industry and academia. To apply finite-domain constrain...
Alan M. Frisch, Brahim Hnich, Zeynep Kiziltan, Ian...