989 resultados para Class relations


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Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information is contained in the so-called kernel matrix, a symmetric and positive semidefinite matrix that encodes the relative positions of all points. Specifying this matrix amounts to specifying the geometry of the embedding space and inducing a notion of similarity in the input space - classical model selection problems in machine learning. In this paper we show how the kernel matrix can be learned from data via semidefinite programming (SDP) techniques. When applied to a kernel matrix associated with both training and test data this gives a powerful transductive algorithm -using the labeled part of the data one can learn an embedding also for the unlabeled part. The similarity between test points is inferred from training points and their labels. Importantly, these learning problems are convex, so we obtain a method for learning both the model class and the function without local minima. Furthermore, this approach leads directly to a convex method for learning the 2-norm soft margin parameter in support vector machines, solving an important open problem.

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Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information is contained in the so-called kernel matrix, a symmetric and positive definite matrix that encodes the relative positions of all points. Specifying this matrix amounts to specifying the geometry of the embedding space and inducing a notion of similarity in the input space -- classical model selection problems in machine learning. In this paper we show how the kernel matrix can be learned from data via semi-definite programming (SDP) techniques. When applied to a kernel matrix associated with both training and test data this gives a powerful transductive algorithm -- using the labelled part of the data one can learn an embedding also for the unlabelled part. The similarity between test points is inferred from training points and their labels. Importantly, these learning problems are convex, so we obtain a method for learning both the model class and the function without local minima. Furthermore, this approach leads directly to a convex method to learn the 2-norm soft margin parameter in support vector machines, solving another important open problem. Finally, the novel approach presented in the paper is supported by positive empirical results.

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We analyze the regional distribution of different categories of creative individuals in Germany. Generally, the share of creative people is higher in cities as compared to the rural area The freelancing artists are a kind of exception in this respect; they constitute a relatively high share of the population in some rural area A high share of creative people in a region can be explained by a high level of public provisions and a high share of foreign born population, which can be regarded as an indicator of the “openness” in the local milieu. Good employment opportunities have only a relatively weak impact. Regions with a high share of creatives tend to have an above average level of new business formation, a high level of innovation and a relatively high share of employees in high-tech industries.

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Public relations educators need new solutions to prepare students to become tomorrow's practitioner today. Managers and employers in the new creative workforce (McWilliam, 2008) expect graduates to be problem solvers, critical and creative thinkers, reflective, and self reliant (Barrie, 2008; David, 2004). Enabling students to develop these attributes requires a collaborative and creative approach to pedagogy (Jeffrey & Craft, 2001, 2004). A model for the next generation of public relations education was developed to integrate industry partnerships as a way to bridge pedagogy and professional practice. The model suggests (a) that industry partnerships be embedded in learning activities, (b) that assessment items be considered on a continuum and delivered incrementally across a course of study, and (c) that connections between classroom and workplace activities are clearly signposted for students.

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The paper examines the situation of postgraduate international students studying in Australia, mostly at doctoral level; a group widely seen as sought-after by Australian universities and employers, though also exposed to difficulties in aspects like learning culture, language and temporary employment. The investigation follows a novel path, as an exercise in practice-led research on issues involved in Higher Degree supervision. It is in fact an exercise within an advanced program of professional development for HD research supervisors. It begins by deploying a journalistic method, to obtain and present information. This has entailed the publishing of two feature articles about the lives of scholars for Subtropic, a campus based online magazine in Brisbane, www.subtropic.com.au. The next step is a review of a set of supervisions, citing issues raised in individual cases. Parallels can be seen between the two information-getting and analytical processes, with scope for contradictions. An exegetical statement deals with supervisory issues that have been exposed, and implications for learning, with recommendations for developing the quality of the experience of these students.

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In recent decades, assessment practices within Australian law schools have moved from the overwhelming use of end-of-year closed-book examinations to an increase in the use of a wider range of techniques. This shift is often characterised as providing a ‘better’ learning environment for students, contributing more positively to their own ‘personal development’ within higher education, or, considered along the lines of critical legal thought, as ‘liberating’ them from the ‘conservatising’ and ‘indoctrinating’ effects of the power relations that operate in law schools. This paper seeks to render problematic such liberal-progressive narratives about these changes to law school assessment practices. It will do so by utilising the work of French historian and philosopher Michel Foucault on power, arguing that the current range of assessment techniques demonstrates a shift in the ‘economy’ of power relations within the law school. Rather than ‘liberating’ students from relations of power, these practices actually extend the power relations through which students are governed. This analysis is intended to inform legal education research and assessment practice by providing a far more nuanced conceptual framework than one that seeks to ‘free’ law students from these ‘repressive’ practices, or hopes to ‘objectively’ contribute to their ‘personal development’.

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A study of crowds drawn to Australian football matches in colonial Victoria illuminates key aspects of the code's genesis, development and popularity. Australian football was codified by a middle-class elite that, as in Britain, created forms of mass entertainment that were consistent with the kind of industrial capitalist society they were attempting to organise. But the 'lower orders' were inculcated with traditional British folkways in matters of popular amusement, and introduced a style of 'barracking' for this new code that resisted the hegemony of the elite football administrators. By the end of the colonial period Australian football was firmly entrenched as a site of contestation between plebeian and bourgeois codes of spectating that reflected the social and ethnic diversity of the clubs making up the Victorian competition. Australian football thereby offers a classic vignette in the larger history of 'resistance through ritual'.

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The multifractal properties of two indices of geomagnetic activity, D st (representative of low latitudes) and a p (representative of the global geomagnetic activity), with the solar X-ray brightness, X l , during the period from 1 March 1995 to 17 June 2003 are examined using multifractal detrended fluctuation analysis (MF-DFA). The h(q) curves of D st and a p in the MF-DFA are similar to each other, but they are different from that of X l , indicating that the scaling properties of X l are different from those of D st and a p . Hence, one should not predict the magnitude of magnetic storms directly from solar X-ray observations. However, a strong relationship exists between the classes of the solar X-ray irradiance (the classes being chosen to separate solar flares of class X-M, class C, and class B or less, including no flares) in hourly measurements and the geomagnetic disturbances (large to moderate, small, or quiet) seen in D st and a p during the active period. Each time series was converted into a symbolic sequence using three classes. The frequency, yielding the measure representations, of the substrings in the symbolic sequences then characterizes the pattern of space weather events. Using the MF-DFA method and traditional multifractal analysis, we calculate the h(q), D(q), and τ (q) curves of the measure representations. The τ (q) curves indicate that the measure representations of these three indices are multifractal. On the basis of this three-class clustering, we find that the h(q), D(q), and τ (q) curves of the measure representations of these three indices are similar to each other for positive values of q. Hence, a positive flare storm class dependence is reflected in the scaling exponents h(q) in the MF-DFA and the multifractal exponents D(q) and τ (q). This finding indicates that the use of the solar flare classes could improve the prediction of the D st classes.

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Though stadium style seating in large lecture theatres may suggest otherwise, effective teaching and learning is a not a spectator sport. A challenge in creating effective learning environments in both physical and virtual spaces is to provide optimal opportunity for student engagement in active learning. Queensland University of Technology (QUT) has developed the Open Web Lecture (OWL), a new web-based student response application, which seamlessly integrates a virtual learning environment within the physical learning space. The result is a blended learning experience; a fluid collaboration between academic and students connected to OWL via the University’s Wi-Fi using their own laptop or mobile web device. QUT is currently piloting the OWL application to encourage student engagement. OWL offers opportunities for participants to: • Post comments and questions • Reply to comments
 • "Like" comments
 • Poll students and review data • Review archived sessions. Many of these features instinctively appeal to student users of social networking media, yet avail the academic of control within the University network. Student privacy is respected through a system of preserving peer-peer anonymity, a functionality that seeks to address a traditional reluctance to speak up in large classes. The pilot is establishing OWL as an opportunity for engaging students in active learning opportunities by enabling • virtual learning in physical spaces for large group lectures, seminar groups, workshops and conferences • live collaborative technology connecting students and the academic via the wireless network using their own laptop or mobile device • an non- intimidating environment in which to ask questions • promotion of a sense of community • instant feedback • problem based learning. The student and academic response to OWL has been overwhelmingly positive, crediting OWL as an easy to use application, which creates effective learning opportunities though interactivity and immediate feedback. This poster and accompanying online presentation of the technology will demonstrate how OWL offers new possibilities for active learning in physical spaces by: • providing increased opportunity for student engagement • supporting a range of learners and learning activities • fostering blended learning experiences. The presentation will feature visual displays of the technology, its various interfaces and feedback including clips from interviews with students and academics participating in the early stages of the pilot.

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ORIGO Stepping Stones gives mathematics teachers the best of both worlds by delivering lessons and teacher guides on a digital platform blended with the more traditional printed student journals. This uniquely interactive program allows students to participate in exciting learning activites whilst still allowing the teacher to maintain control of learning outcomes. It is the first program in Australia to give teachers activities to differentiate instruction within each lesson and across school years. Written by a team of Australia's leading mathematics educators, this program integrates key research findings in a practical sequence of modules and lessons providing schools with a step-by-step approach to the new curriculum. Click links on the right to explore the program.