Partitioning graphs into equally large groups of nodes while minimizing the number of edges between di erent groups is an extremely important problem in parallel computing. For instance, e ciently parallelizing several scienti c and engineering applications requires the partitioning of data or tasks among processors such that the computational load on each node is roughly the same, while commun...

Subgroup analysis is an integral part of comparative analysis where assessing the treatment effect on a response is of central interest. Its goal is to determine the heterogeneity of the treatment effect across subpopulations. In this paper, we adapt the idea of recursive partitioning and introduce an interaction tree (IT) procedure to conduct subgroup analysis. The IT procedure automatically f...

Hyperfine splitting in Bi 82+ and Pb 81+ ions was calculated using continuum RPA approach with effective residual forces. To fix the parameters of the theory the nuclear magnetic dipole moments of two one-particle and two one-hole nuclei around 208 Pb were calculated using the same approach. The contribution from velocity dependent two-body spin-orbit residual interaction was calculated explici...

The objective of this study is to conduct a comprehensive assessment of the transport of isoxaflutole and RPA 202248 and their accumulation potential in semistatic water bodies, using a distributed watershed scale model and observed water quality data. A conceptual model was developed to characterize the fate and transport of isoxaflutole residues to and in surface water. The soil and water ass...

This paper deals with the k-way ratio cut hypergraph partitioning utilizing the Mixed discrete continuous variant of the Bayesian Optimization Algorithm (mBOA). We have tested our algorithm on three partitioning taxonomies: recursive minimum ratio cut, multi-way minimum ratio cut and recursive minimum cut bisection. We have also derived a new approach for modeling of Boolean functions using bin...

A variety of new statistical methods from the field of machine learning have the potential to offer new impulses for research in the social, educational and behavioral sciences. In this article we focus on one of these methods: model-based recursive partitioning. This algorithmic approach is reviewed and illustrated by means of instructive examples and an application to the Mincer equation. For...

In this paper, we analyze the second eigenvector technique of spectral partitioning on the planted partition random graph model, by constructing a recursive algorithm using the second eigenvectors in order to learn the planted partitions. The correctness of our algorithm is not based on the ratio-cut interpretation of the second eigenvector, but exploits instead the stability of the eigenvector...

Adaptive partitioning of a multidimensional feature space plays a fundamental role in the design of data-compression schemes. Most partition-based design methods operate in an iterative fashion, seeking to reduce distortion at each stage of their operation by implementing a linear split of a selected cell. The operation and eventual outcome of such methods is easily described in terms of binary...

We study normalization problems associated with use of perturbatively correlated ground-states in extended RPA schemes in the context of a specific but typical example. The sensitivity of the results to the amount of 2p2h admixtures to the correlated ground state is also investigated in terms of a modification of the standard perturbative approach.

Linear response theory for the density matrix renormalization group (DMRG-LRT) was first presented in terms of the DMRG renormalization projectors [J. J. Dorando, J. Hachmann, and G. K.-L. Chan, J. Chem. Phys. 130, 184111 (2009)]. Later, with an understanding of the manifold structure of the matrix product state (MPS) ansatz, which lies at the basis of the DMRG algorithm, a way was found to con...