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  Load and Attentional Bayes

Dayan, P. (2009). Load and Attentional Bayes. In D. Koller, D. Schuurmans, Y. Bengio, & L. Bottou (Eds.), Advances in neural information processing systems 21 (pp. 370-377). Red Hook, NY, USA: Curran.

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 Creators:
Dayan, P1, Author              
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1External Organizations, ou_persistent22              

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 Abstract: Selective attention is a most intensively studied psychological phenomenon, rife with theoretical suggestions and schisms. A critical idea is that of limited capacity, the allocation of which has produced continual conflict about such phenomena as early and late selection. An influential resolution of this debate is based on the notion of perceptual load (Lavie, 2005), which suggests that low-load, easy tasks, because they underuse the total capacity of attention, mandatorily lead to the processing of stimuli that are irrelevant to the current attentional set; whereas high-load, difficult tasks grab all resources for themselves, leaving distractors high and dry. We argue that this theory presents a challenge to Bayesian theories of attention, and suggest an alternative, statistical, account of key supporting data.

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 Dates: 2009-06
 Publication Status: Published in print
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Title: Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS 2008)
Place of Event: Vancouver, BC, Canada
Start-/End Date: 2008-12-08 - 2008-12-10

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Title: Advances in neural information processing systems 21
Source Genre: Proceedings
 Creator(s):
Koller, D, Editor
Schuurmans, D, Editor
Bengio, Y, Editor
Bottou, L, Editor
Affiliations:
-
Publ. Info: Red Hook, NY, USA : Curran
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 370 - 377 Identifier: ISBN: 978-1-60560-949-2