In this paper we describe a generic library of problemsolving methods (PSMs) for scheduling applications. Although, some attempts have been made in the past at developing librarie...
Dnyanesh G. Rajpathak, Enrico Motta, Zdenek Zdr&aa...
Abstract. Learning in the context of constraint solving is a technique by which previously unknown constraints are uncovered during search and used to speed up subsequent search. R...
Ian P. Gent, Christopher Jefferson, Lars Kotthoff,...
Multidimensional analysis allows decision makers to efficiently and effectively use data analysis tools, which mainly depend on multidimensional (MD) structures of a data warehous...
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...
We show how variational Bayesian inference can be implemented for very large generalized linear models. Our relaxation is proven to be a convex problem for any log-concave model. ...