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    Using Bad Learners to find Good Configurations

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    Finding the optimally performing configuration of a software system for a given setting is often challenging. Recent approaches address this challenge by learning performance models based on a sample set of configurations. However, building an accurate performance model can be very expensive (and is often infeasible in practice). The central insight of this paper is that exact performance values (e.g. the response time of a software system) are not required to rank configurations and to identify the optimal one. As shown by our experiments, models that are cheap to learn but inaccurate (with respect to the difference between actual and predicted performance) can still be used rank configurations and hence find the optimal configuration. This novel \emph{rank-based approach} allows us to significantly reduce the cost (in terms of number of measurements of sample configuration) as well as the time required to build models. We evaluate our approach with 21 scenarios based on 9 software systems and demonstrate that our approach is beneficial in 16 scenarios; for the remaining 5 scenarios, an accurate model can be built by using very few samples anyway, without the need for a rank-based approach.Comment: 11 pages, 11 figure

    Combining Student-based Learning Activities with Teacher's Encouragements to Foster Learner Autonomy in Elt

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    Teacher's domination and authority used to prevail the traditional language teaching is now left and replaced by more acceptable concept of teaching. This concept emphasizes on developing the sense of learners' responsibility, independence, or autonomy, for better learning outcome. Autonomous language learners are those assumed to have greater responsibility on their own learning for their own needs. A series of guided practice through a step-by-step manner is needed in order that students can be possibly trained to be autonomous, independent learners. This paper discusses learning activities created and designed by the students combined with teacher's encouragements to foster learner autonomy. Some theories and previous studies on learner autonomy are analyzed to support the discussion. It is believed that the combination between the two important aspects in autonomous language learning will strengthen the efforts of promoting learner autonomy in ELT. Keywords: English language teaching, learner autonomy, autonomous learning, learning activities, teacher's encouragemen

    Combining Undersampled Dithered Images

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    Undersampled images, such as those produced by the HST WFPC-2, misrepresent fine-scale structure intrinsic to the astronomical sources being imaged. Analyzing such images is difficult on scales close to their resolution limits and may produce erroneous results. A set of ``dithered'' images of an astronomical source generally contains more information about its structure than any single undersampled image, however, and may permit reconstruction of a ``superimage'' with Nyquist sampling. I present a tutorial on a method of image reconstruction that builds a superimage from a complex linear combination of the Fourier transforms of a set of undersampled dithered images. This method works by algebraically eliminating the high order satellites in the periodic transforms of the aliased images. The reconstructed image is an exact representation of the data-set with no loss of resolution at the Nyquist scale. The algorithm is directly derived from the theoretical properties of aliased images and involves no arbitrary parameters, requiring only that the dithers are purely translational and constant in pixel-space over the domain of the object of interest. I show examples of its application to WFC and PC images. I argue for its use when the best recovery of point sources or morphological information at the HST diffraction limit is of interest.Comment: 22 pages, 9 EPS figures, submitted to PAS

    Combining Voting Rules Together

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    We propose a simple method for combining together voting rules that performs a run-off between the different winners of each voting rule. We prove that this combinator has several good properties. For instance, even if just one of the base voting rules has a desirable property like Condorcet consistency, the combination inherits this property. In addition, we prove that combining voting rules together in this way can make finding a manipulation more computationally difficult. Finally, we study the impact of this combinator on approximation methods that find close to optimal manipulations
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