Kernelized design of experiments

This paper describes an approach for selecting instances in regression problems in the cases where observations x are readily available, but obtaining labels y is hard. Given a database of observations, an algorithm inspired by statistical design of experiments and kernel methods is presented that selects a set of k instances to be chosen in order to maximize the prediction performance of a support vector machine. It is shown that the algorithm significantly outperforms related approaches on a number of real-world datasets. --

Collective bargaining structure and its determinants : an empirical analysis with British and German establishment data

"Using two nationally representative establishment data sets, this paper investigates collective bargaining coverage and firms' choice of governance structures for the employment relationship in Britain and in (western and eastern) Germany. Both countries have experienced a substantial decline in collective bargaining coverage in the last decades. While bargaining coverage is generally lower in Britain, single-employer bargaining is relatively more important in Britain, whereas multi-employer collective bargaining clearly dominates in Germany. Econometric analyses show that more or less the same set of variables play a statistically significant role in explaining the structure of collective bargaining in both countries. These include establishment size, establishment age, foreign ownership, public sector affiliation and being a branch plant." (Author's abstract, IAB-Doku) ((en))Tarifverhandlungen - internationaler Vergleich, Tarifautonomie, Tarifpartner, Tarifbindung, Tarifverhandlungen - Determinanten, Betriebsvereinbarung, Flächentarifvertrag, Dezentralisation, IAB-Betriebspanel, Unternehmensgröße, Betriebsgröße, Wirtschaftszweige, Arbeitsbeziehungen, Unternehmenspolitik, Unternehmensführung, Unternehmensalter, öffentlicher Dienst, ausländische Arbeitgeber, regionaler Vergleich, Firmentarifvertrag, Tarifbindung, Bundesrepublik Deutschland, Großbritannien, Ostdeutschland, Westdeutschland

Viral evolution under the pressure of an adaptive immune system - optimal mutation rates for viral escape

Based on a recent model of evolving viruses competing with an adapting immune system [1], we study the conditions under which a viral quasispecies can maximize its growth rate. The range of mutation rates that allows viruses to thrive is limited from above due to genomic information deterioration, and from below by insufficient sequence diversity, which leads to a quick eradication of the virus by the immune system. The mutation rate that optimally balances these two requirements depends to first order on the ratio of the inverse of the virus' growth rate and the time the immune system needs to develop a specific answer to an antigen. We find that a virus is most viable if it generates exactly one mutation within the time it takes for the immune system to adapt to a new viral epitope. Experimental viral mutation rates, in particular for HIV (human immunodeficiency virus), seem to suggest that many viruses have achieved their optimal mutation rate. [1] C.Kamp and S. Bornholdt, Phys. Rev. Lett., 88, 068104 (2002)Comment: 5 pages RevTeX including 3 figure

A jigsaw puzzle framework for homogenization of high porosity foams

An approach to homogenization of high porosity metallic foams is explored. The emphasis is on the \Alporas{} foam and its representation by means of two-dimensional wire-frame models. The guaranteed upper and lower bounds on the effective properties are derived by the first-order homogenization with the uniform and minimal kinematic boundary conditions at heart. This is combined with the method of Wang tilings to generate sufficiently large material samples along with their finite element discretization. The obtained results are compared to experimental and numerical data available in literature and the suitability of the two-dimensional setting itself is discussed.Comment: 11 pages, 7 figures, 3 table

D-optimal plans in observational studies

This paper investigates the use of Design of Experiments in observational studies in order to select informative observations and features for classification. D-optimal plans are searched for in existing data and based on these plans the variables most relevant for classification are determined. The adapted models are then compared with respect to their predictive accuracy on an independent test sample. Eight different data sets are investigated by this method. --D-optimality,Genetic Algorithm,Prototypes,Feature Selection

Kernelized design of experiments

This paper describes an approach for selecting instances in regression problems in the cases where observations x are readily available, but obtaining labels y is hard. Given a database of observations, an algorithm inspired by statistical design of experiments and kernel methods is presented that selects a set of k instances to be chosen in order to maximize the prediction performance of a support vector machine. It is shown that the algorithm significantly outperforms related approaches on a number of real-world datasets

Probing atom-surface interactions by diffraction of Bose-Einstein condensates

In this article we analyze the Casimir-Polder interaction of atoms with a solid grating and an additional repulsive interaction between the atoms and the grating in the presence of an external laser source. The combined potential landscape above the solid body is probed locally by diffraction of Bose-Einstein condensates. Measured diffraction efficiencies reveal information about the shape of the Casimir-Polder interaction and allow us to discern between models based on a pairwise-summation (Hamaker) approach and Lifshitz theory.Comment: 5 pages, 4 figure