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Algorithms for learning Bayesian networks from data have two components: a scoring metric and a search procedure. The scoring… Expand We present a model for computation over the reals or an arbitrary (ordered) ring R. In this general setting, we obtain universal… Expand AbstractIn continuous variable, smooth, nonconvex nonlinear programming, we analyze the complexity of checking whether(a)a given… Expand We show that it is NP-complete to determine the chromatic index of an arbitrary graph. The problem remains NP-complete even for… Expand We show that the following problem is NP-complete. Given a graph, find the minimum number of edges (fill-in) whose addition makes… Expand This paper was motivated by a practical problem related to databases for image processing: given a set of points in the plane… Expand An optimum rectilinear Steiner tree for a set A of points in the plane is a tree which interconnects A using horizontal and… Expand We demonstrate that cons&g optimal binary de&ion trees ia an NP=compkt.e probtem, where an op timal tree is one which minin&s the… Expand We show that the problem of finding an optimal schedule for a set of jobs is NP-complete even in the following two restricted… Expand It is widely believed that showing a problem to be NP-complete is tantamount to proving its computational intractability. In this… Expand