997 resultados para Art, Medieval.


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Watt, P., Medieval Women's Writing (Cambridge: Polity Press, 2007) RAE2008

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Sexton, J. (2008). From Art to Avant Garde? Television, Formalism and the Arts Documentary in 1960's Britain. In L. Mulvey and J. Sexton (Eds.), Experimental British Television (pp.89-105). Manchester: Manchester University Press. RAE2008

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Hughes, I. (2006). The Four Branches of the Mabinogi and Medieval Welsh Poetry. Studi Celtici. 4, pp.155-193. RAE2008

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Haycock, Marged, 'Sy abl fodd Sibli fain: Sibyl in Medieval Wales', In: Heroic Poets and Poetic Heroes in Celtic Tradition, Joseph Falaky Nagy and Leslie Ellen Jones (eds), (Dublin: Four Courts Press), pp.115-130, 2005 RAE2008

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Rodway, S. (2007). The Where, Who, When and Why of Medieval Welsh Prose Texts: Some Methodological Considerations. Studia Celtica. 41, pp.47-89. RAE2008

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Schofield, Phillipp, and N. J. Mayhew, eds., Credit and Debt in medieval England, c.1180-c.1350 (Oxford: Oxbow Books, 2002), pp.x+164 RAE2008

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New, Elizabeth, 'Signs of community or marks of the exclusive? Parish and guild seals in later medieval England', In: The Parish in Late Medieval England, (Lincs: Shaun Tyas) pp.112-128, 2006 RAE2008

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St?ber, Karen. 'The role of late medieval English monasteries as expressions of patronal authority: some case studies', in: 'The Use and Abuse of Sacred Places in Late Medieval Towns, Medievalia Lovaniensia, Series I, Studia XXXVIII', (Leuven: Leuven University Press), pp.189-207, 2006 RAE2008

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Schofield, Phillipp, Peasant and Community in medieval England, 1200-1500 (New York: Palgrave Macmillan, 2003), pp.vii+279 RAE2008

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New, E. (2002). Christological personal seals and Christocentric devotion in later medieval England and Wales. Antiquaries Journal. 82, pp.47-68. RAE2008

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Rothwell, W., 'Synonymity and Semantic Variability in Medieval French and Middle English', Modern Language Review (2007) 102(2) pp.363-380 RAE2008

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ACT is compared with a particular type of connectionist model that cannot handle symbols and use non-biological operations that cannot learn in real time. This focus continues an unfortunate trend of straw man "debates" in cognitive science. Adaptive Resonance Theory, or ART, neural models of cognition can handle both symbols and sub-symbolic representations, and meets the Newell criteria at least as well as these models.

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Memories in Adaptive Resonance Theory (ART) networks are based on matched patterns that focus attention on those portions of bottom-up inputs that match active top-down expectations. While this learning strategy has proved successful for both brain models and applications, computational examples show that attention to early critical features may later distort memory representations during online fast learning. For supervised learning, biased ARTMAP (bARTMAP) solves the problem of over-emphasis on early critical features by directing attention away from previously attended features after the system makes a predictive error. Small-scale, hand-computed analog and binary examples illustrate key model dynamics. Twodimensional simulation examples demonstrate the evolution of bARTMAP memories as they are learned online. Benchmark simulations show that featural biasing also improves performance on large-scale examples. One example, which predicts movie genres and is based, in part, on the Netflix Prize database, was developed for this project. Both first principles and consistent performance improvements on all simulation studies suggest that featural biasing should be incorporated by default in all ARTMAP systems. Benchmark datasets and bARTMAP code are available from the CNS Technology Lab Website: http://techlab.bu.edu/bART/.

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In this paper, we introduce the Generalized Equality Classifier (GEC) for use as an unsupervised clustering algorithm in categorizing analog data. GEC is based on a formal definition of inexact equality originally developed for voting in fault tolerant software applications. GEC is defined using a metric space framework. The only parameter in GEC is a scalar threshold which defines the approximate equality of two patterns. Here, we compare the characteristics of GEC to the ART2-A algorithm (Carpenter, Grossberg, and Rosen, 1991). In particular, we show that GEC with the Hamming distance performs the same optimization as ART2. Moreover, GEC has lower computational requirements than AR12 on serial machines.