The finite element method is a numerical simulation technique for solving partial differential equations. Domain decomposition provides a means for parallelizing the expensive simulation with modern computing architecture. Choosing the sub-domains for domain decomposition is a non-trivial task, and in this paper we show how this can be addressed with machine learning. Our method starts with a b...

Bertschinger, Rauh, Olbrich, Jost, and Ay (Entropy, 2014) have proposed a definition of a decomposition of the mutual information MI(X : Y, Z) into shared, synergistic, and unique information by way of solving a convex optimization problem. In this paper, we discuss the solution of their Convex Program from theoretical and practical points of view.

The partial fraction decomposition of a proper rational function whose denominator has degree n and is given in general factored form can be 2 done in 0(n log n) operations in the worst case. Previous algorithms 3 2 require 0(n ) operations, and 0(n log n) operations for the special case where the factors appearing in the denominator are all linear.

We consider the covariant Spectator equation with a One Boson Exchange (OBE) kernel, and apply it to the NN system. Relativistic effects such as retardation and negative-energy state components are included in that equation. We develop a method, based on the Padé method, to solve the Spectator equation without partial wave decomposition. The convergence of the partial wave decomposition series ...

We describe DPOCL, a partinl-order csnsal llnk planner that includes action decomposition. DPOCL builds directly on the SNLP algorithm (McAllester Rosenbiltt 1991), and hence is clear and simple, ud can readily be integrated with other SNLP extensions. In addition, DPOCL is specifically designed to handle partially specified action decompositions. Plan generation in DPOCL exploits the planner’s...