Analysis of the (μ/μI,λ)(\mu/\mu_I,\lambda)-CSA-ES with Repair by Projection Applied to a Conically Constrained Problem

Theoretical analyses of evolution strategies are indispensable for gaining a deep understanding of their inner workings. For constrained problems, rather simple problems are of interest in the current research. This work presents a theoretical analysis of a multi-recombinative evolution strategy with cumulative step size adaptation applied to a conically constrained linear optimization problem. The state of the strategy is modeled by random variables and a stochastic iterative mapping is introduced. For the analytical treatment, fluctuations are neglected and the mean value iterative system is considered. Non-linear difference equations are derived based on one-generation progress rates. Based on that, expressions for the steady state of the mean value iterative system are derived. By comparison with real algorithm runs, it is shown that for the considered assumptions, the theoretical derivations are able to predict the dynamics and the steady state values of the real runs.Comment: This is a PREPRINT of an article that has been accepted for publication in the journal MIT Press Evolutionary Computation (ECJ). 25 pages + supplementary material. The work was supported by the Austrian Science Fund FWF under grant P29651-N3

A History of Cluster Analysis Using the Classification Society's Bibliography Over Four Decades

The Classification Literature Automated Search Service, an annual bibliography based on citation of one or more of a set of around 80 book or journal publications, ran from 1972 to 2012. We analyze here the years 1994 to 2011. The Classification Society's Service, as it was termed, has been produced by the Classification Society. In earlier decades it was distributed as a diskette or CD with the Journal of Classification. Among our findings are the following: an enormous increase in scholarly production post approximately 2000; a very major increase in quantity, coupled with work in different disciplines, from approximately 2004; and a major shift also from cluster analysis in earlier times having mathematics and psychology as disciplines of the journals published in, and affiliations of authors, contrasted with, in more recent times, a "centre of gravity" in management and engineering.Comment: 23 pages, 9 figure

What Drives Students' Loyalty-Formation in Social Media Learning Within a Personal Learning Environment Approach? The Moderating Role of Need for Cognition

Our study analyzes an educational experience based on the integrated use of social media within a higher education course under a personal learning environment approach and investigates the factors that determine students' loyalty to social media learning. We examined the moderating role of need for cognition (NFC) in students' formation of attitudes, satisfaction, and loyalty toward this learning experience. The results indicate that NFC has an influence on these variables, significantly moderating how loyalty toward social media learning is formed. For high-NFC students, satisfaction with the learning experience is the most important variable to explain loyalty; whereas for low-NFC students, attitudes have a stronger effect. Different strategies are suggested, according to the learners' NFC levels, for increasing the use of social media in personal learning environments. Practical implications for improving the integration of such informal resources into formal education are discussed.Junta de Andalucía – Programa Andaluz de I + D P12 SEJ 259

Fully coherent follow-up of continuous gravitational-wave candidates

The search for continuous gravitational waves from unknown isolated sources is computationally limited due to the enormous parameter space that needs to be covered and the weakness of the expected signals. Therefore semi-coherent search strategies have been developed and applied in distributed computing environments such as Einstein@Home, in order to narrow down the parameter space and identify interesting candidates. However, in order to optimally confirm or dismiss a candidate as a possible gravitational-wave signal, a fully-coherent follow-up using all the available data is required. We present a general method and implementation of a direct (2-stage) transition to a fully-coherent follow-up on semi-coherent candidates. This method is based on a grid-less Mesh Adaptive Direct Search (MADS) algorithm using the F-statistic. We demonstrate the detection power and computing cost of this follow-up procedure using extensive Monte-Carlo simulations on (simulated) semi-coherent candidates from a directed as well as from an all-sky search setup.Comment: 12 pages, 5 figure