Recently, eigenvector localization of complex network has seen a spurt in activities due to its versatile applicability in many different areas which includes networks centrality measure, spectral partitioning, development of approximation algorithms and disease spreading phenomenon. For a network, an eigenvector is said to be localized when most of its components are near to zero, with few tak...

1 Toward A Confidence Estimate For The Most-Central-Actor Finding Terrill L. Frantz & Kathleen M. Carley ABSTRACT We introduce a innovative practice of providing a statistical confidence estimate to accompany the reporting of the most-central actor according to social network data; often times, collected relationship-data has some amount of error, which may affect the accuracy of the topactor f...

This chapter proposes a novel approach to credit risk rating based upon Network Analysis and enabled by Human Computation. Credit risk rating, which is essential on financial markets, has become difficult with the advent of financial instruments called derivatives and structured notes and of credit management techniques called securitization. The consequences have been dramatic: A widespread im...

In this paper, we propose a new eigenvector-based line feature matching algorithm, which is invariant to the in-plane rotation, translation, and scale. First, in order to reduce the number of possible matches, we use a preliminary correspondence test that generates a set of finite candidate models, by restricting combinations of line features in the input image. This approach resolves an inhere...

Christian F. A. Negre, ∗ Heidi Hendrickson, Rhitankar Pal, Ivan Rivalta, † Junming Ho, and Victor S. Batista ‡ Theoretical Divission, Los Alamos National Laboratory, Los Alamos, NM 87545 Department of Chemistry, Yale University, P.O. Box 208107, New Haven, CT 06520-8107, and Energy Sciences Institute, Yale University, P.O. Box 27394, West Haven, CT 06516-7394 École Normale Supérieure de Lyon, C...

We develop an extension of eigenvector continuation (EC) that makes it possible to extrapolate simulations quantum systems in finite periodic boxes across large ranges box sizes. The formal justification for this approach, which we call finite-volume (FVEC), is provided by matching functions at different As concrete FVEC implementation use a discrete variable representation based on plane-wave ...

The Riesz basis property of the generalized eigenvector system of a Timoshenko beam with boundary feedback is studied. Firstly, two auxiliary operators are introduced, and the Riesz basis property of their eigenvector systems is proved. This property is used to show that the generalized eigenvector system of a Timoshenko beam with some linear boundary feedback forms a Riesz basis in the corresp...

The dips of boundaries in faults and caldera walls play an important role in understanding their formation mechanisms. The fault dip is a particularly important parameter in numerical simulations for hazard map creation as the fault dip affects estimations of the area of disaster occurrence. In this study, I introduce a technique for estimating the fault dip using the eigenvector of the observe...

We develop a new method for estimating and removing the spectrum of the sky from deep spectroscopic observations. Our method does not rely on simultaneous measurement of the sky spectrum with the object spectrum. The technique is based on the iterative subtraction of continuum estimates and eigenvector sky models derived from singular value decompositions of sky spectra and sky spectra residual...