6,624 research outputs found

    Citation Statistics

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    This is a report about the use and misuse of citation data in the assessment of scientific research. The idea that research assessment must be done using ``simple and objective'' methods is increasingly prevalent today. The ``simple and objective'' methods are broadly interpreted as bibliometrics, that is, citation data and the statistics derived from them. There is a belief that citation statistics are inherently more accurate because they substitute simple numbers for complex judgments, and hence overcome the possible subjectivity of peer review. But this belief is unfounded.Comment: This paper commented in: [arXiv:0910.3532], [arXiv:0910.3537], [arXiv:0910.3543], [arXiv:0910.3546]. Rejoinder in [arXiv:0910.3548]. Published in at http://dx.doi.org/10.1214/09-STS285 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

    Rejoinder: Citation Statistics

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    Rejoinder to "Citation Statistics" [arXiv:0910.3529]Comment: Published in at http://dx.doi.org/10.1214/09-STS285REJ the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

    On the Completeness of Spider Diagrams Augmented with Constants

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    Diagrammatic reasoning can be described formally by a number of diagrammatic logics; spider diagrams are one of these, and are used for expressing logical statements about set membership and containment. Here, existing work on spider diagrams is extended to include constant spiders that represent specific individuals. We give a formal syntax and semantics for the extended diagram language before introducing a collection of reasoning rules encapsulating logical equivalence and logical consequence. We prove that the resulting logic is sound, complete and decidable

    We Know More Than We Are, At First, Prepared To Acknowledge: Journeying to Develop Critical Thinking

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    Exponents of critical thinking emphasize the teaching of skills and dispositions for scrutinizing the assumptions, reasoning, and evidence brought to bear on an issue by others and by oneself. In short, they promote thinking about thinking. But how do students come to see where there are issues to be opened up and identify them without relying on some authority? The current form of my evolving answer is that people need support to grapple with inevitable tensions in personal and intellectual development—support to undertake journeys that involve risk, open up questions, create more experiences than can be integrated at first sight, require support, and yield personal change. In this essay I present five passages in a pedagogical journey that has led from teaching undergraduate science-in-society courses to running a graduate program in critical thinking and reflective practice for teachers and other mid-career professionals. I have shaped these passages to expose some of my conceptual and practical struggles in learning to decenter pedagogy and to provide space and support for students to develop as critical thinkers. The key challenge I highlight is of helping people make knowledge and practice from insights and experience that they are not prepared, at first, to acknowledge. In a self-exemplifying style, each passage raises some questions for further inquiry or discussion. My hope is that the essay as a whole stimulates readers to grapple with issues they were not aware they faced and to generate questions beyond those I present

    PAC-Bayesian Analysis of Martingales and Multiarmed Bandits

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    We present two alternative ways to apply PAC-Bayesian analysis to sequences of dependent random variables. The first is based on a new lemma that enables to bound expectations of convex functions of certain dependent random variables by expectations of the same functions of independent Bernoulli random variables. This lemma provides an alternative tool to Hoeffding-Azuma inequality to bound concentration of martingale values. Our second approach is based on integration of Hoeffding-Azuma inequality with PAC-Bayesian analysis. We also introduce a way to apply PAC-Bayesian analysis in situation of limited feedback. We combine the new tools to derive PAC-Bayesian generalization and regret bounds for the multiarmed bandit problem. Although our regret bound is not yet as tight as state-of-the-art regret bounds based on other well-established techniques, our results significantly expand the range of potential applications of PAC-Bayesian analysis and introduce a new analysis tool to reinforcement learning and many other fields, where martingales and limited feedback are encountered

    Деякі аспекти проблеми підготовки студентів до організації самостійної роботи у коледжах

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    this paper has been twofold. Firstly, we have stated the known results for high confidence bounds on the generalization error of SVMs in terms of the margin and number of support vectors. Secondly, we wanted to highlight that these results can only be obtained from a data-dependent analysis relying as they do on using some measure to estimate how favourable the input distribution is in relation to the target function. This type of analysis is relatively novel [9], but we feel that its potential for motivating algorithms that are able to take advantage of collusions between distribution and target is far from being exhausted. Indeed, we believe that this is frequently an ingredient in successful learning systems which has been exploited by accident. By more careful analysis of this phenomenon it may well be possible to motivate key ingredients in the Support Vector arsenal, such as choice of kernel function, the bound used in the soft-margin approach and so on. We have also given examples to show that the style of analysis is not limited to SVMs but applies to many other learning machines including two of the most effective techniques, boosting and Bayesian methods. Acknowledgements John Shawe-Taylor was supported in part by the EPSRC research grant number GR/K70366. Peter Bartlett was supported by the Australian Research Council. Appendix: Proof of Theorem 1.

    Automatic classification of spectra from the Infrared Astronomical Satellite (IRAS)

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    A new classification of Infrared spectra collected by the Infrared Astronomical Satellite (IRAS) is presented. The spectral classes were discovered automatically by a program called Auto Class 2. This program is a method for discovering (inducing) classes from a data base, utilizing a Bayesian probability approach. These classes can be used to give insight into the patterns that occur in the particular domain, in this case, infrared astronomical spectroscopy. The classified spectra are the entire Low Resolution Spectra (LRS) Atlas of 5,425 sources. There are seventy-seven classes in this classification and these in turn were meta-classified to produce nine meta-classes. The classification is presented as spectral plots, IRAS color-color plots, galactic distribution plots and class commentaries. Cross-reference tables, listing the sources by IRAS name and by Auto Class class, are also given. These classes show some of the well known classes, such as the black-body class, and silicate emission classes, but many other classes were unsuspected, while others show important subtle differences within the well known classes

    Evaluation of forensic DNA traces when propositions of interest relate to activities: analysis and discussion of recurrent concerns

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    When forensic scientists evaluate and report on the probative strength of single DNA traces, they commonly rely on only one number, expressing the rarity of the DNA profile in the population of interest. This is so because the focus is on propositions regarding the source of the recovered trace material, such as “the person of interest is the source of the crime stain.” In particular, when the alternative proposition is “an unknown person is the source of the crime stain,” one is directed to think about the rarity of the profile. However, in the era of DNA profiling technology capable of producing results from small quantities of trace material (i.e., non-visible staining) that is subject to easy and ubiquitous modes of transfer, the issue of source is becoming less central, to the point that it is often not contested. There is now a shift from the question “whose DNA is this?” to the question “how did it get there?” As a consequence, recipients of expert information are now very much in need of assistance with the evaluation of the meaning and probative strength of DNA profiling results when the competing propositions of interest refer to different activities. This need is widely demonstrated in day-to-day forensic practice and is also voiced in specialized literature. Yet many forensic scientists remain reluctant to assess their results given propositions that relate to different activities. Some scientists consider evaluations beyond the issue of source as being overly speculative, because of the lack of relevant data and knowledge regarding phenomena and mechanisms of transfer, persistence and background of DNA. Similarly, encouragements to deal with these activity issues, expressed in a recently released European guideline on evaluative reporting (Willis et al., 2015), which highlights the need for rethinking current practice, are sometimes viewed skeptically or are not considered feasible. In this discussion paper, we select and discuss recurrent skeptical views brought to our attention, as well as some of the alternative solutions that have been suggested. We will argue that the way forward is to address now, rather than later, the challenges associated with the evaluation of DNA results (from small quantities of trace material) in light of different activities to prevent them being misrepresented in court
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