50,510 research outputs found

    Comparative Experiments on Disambiguating Word Senses: An Illustration of the Role of Bias in Machine Learning

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    This paper describes an experimental comparison of seven different learning algorithms on the problem of learning to disambiguate the meaning of a word from context. The algorithms tested include statistical, neural-network, decision-tree, rule-based, and case-based classification techniques. The specific problem tested involves disambiguating six senses of the word ``line'' using the words in the current and proceeding sentence as context. The statistical and neural-network methods perform the best on this particular problem and we discuss a potential reason for this observed difference. We also discuss the role of bias in machine learning and its importance in explaining performance differences observed on specific problems.Comment: 10 page

    Minimalist Solution to Williamson County

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    Williamson County Regional Planning Commission v. Hamilton Bank of Johnson County relegated Fifth Amendment takings claims to a second-class of federal rights. Before a takings plaintiff can sue in federal court, she must first seek compensation through an “adequate state procedure.” Many federal courts have held that requirement to mean a takings litigant must first seek compensation through state courts if that state provides an inverse condemnation proceeding. However, if a takings litigant sues in state court, she will be unable to sue in federal court because of issue preclusion. This effectively shuts the federal courthouse door to many property owners. Only two Supreme Court justices have shown any interest in revisiting Williamson County . Thus, land use attorneys who are concerned about federal court access for takings plaintiffs should craft a case that would attract the Supreme Court’s attention. This Article argues that land use lawyers should present the Court with a case in which the property owner has used a non-judicial procedure to seek compensation (such as asking for compensation from a county board). The Court could then rule that such a non-judicial procedure is an “adequate state procedure” that satisfies Williamson County’ s requirements. This ruling would minimize the negative effects that Williamson County has wrought on takings plaintiffs

    Estimating the Distribution of Dietary Consumption Patterns

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    In the United States the preferred method of obtaining dietary intake data is the 24-hour dietary recall, yet the measure of most interest is usual or long-term average daily intake, which is impossible to measure. Thus, usual dietary intake is assessed with considerable measurement error. We were interested in estimating the population distribution of the Healthy Eating Index-2005 (HEI-2005), a multi-component dietary quality index involving ratios of interrelated dietary components to energy, among children aged 2-8 in the United States, using a national survey and incorporating survey weights. We developed a highly nonlinear, multivariate zero-inflated data model with measurement error to address this question. Standard nonlinear mixed model software such as SAS NLMIXED cannot handle this problem. We found that taking a Bayesian approach, and using MCMC, resolved the computational issues and doing so enabled us to provide a realistic distribution estimate for the HEI-2005 total score. While our computation and thinking in solving this problem was Bayesian, we relied on the well-known close relationship between Bayesian posterior means and maximum likelihood, the latter not computationally feasible, and thus were able to develop standard errors using balanced repeated replication, a survey-sampling approach.Comment: Published in at http://dx.doi.org/10.1214/12-STS413 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org). arXiv admin note: substantial text overlap with arXiv:1107.486

    Geometric Unification of Electromagnetism and Gravitation

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    A recently proposed classical field theory comprised of four field equations that geometrically couple the Maxwell tensor to the Riemann-Christoffel curvature tensor in a fundamentally new way is reviewed and extended. The new theory's field equations show little resemblance to the field equations of classical physics, but both Maxwell's equations of electromagnetism and Einstein's equation of General Relativity augmented by a term that can mimic the properties of dark matter and dark energy are shown to be a consequence. Emphasized is the emergence of gravity and the unification brought to electromagnetic and gravitational phenomena as well as the consistency of solutions of the new theory with those of the classical Maxwell and Einstein field equations. Unique to the four field equations reviewed here and based on specific solutions to them are: the emergence of antimatter and its behavior in gravitational fields, the emergence of dark matter and dark energy mimicking terms in the context of General Relativity, an underlying relationship between electromagnetic and gravitational radiation, the impossibility of negative mass solutions that would generate repulsive gravitational fields or antigravity, and a method for quantizing the charge and mass of particle-like solutions
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