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Activity Number:
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449
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Type:
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Invited
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Date/Time:
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Wednesday, August 5, 2009 : 10:30 AM to 12:20 PM
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Sponsor:
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WNAR
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| Abstract - #302774 |
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Title:
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A Bayesian Theory of Surprise for Modeling Attention Mechanisms in Natural and Artificial Perceptual Systems: Application to Eye Movements
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Author(s):
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Pierre Baldi*+
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Companies:
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University of California, Irvine
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Address:
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Dept. of Computer Science, Irvine, CA, 92697-3435,
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Keywords:
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Abstract:
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The concept of surprise is central to sensory processing, attention, decision making, learning and adaptation. We introduce a Bayesian definition of surprise by measuring the difference between prior and posterior distributions. Surprise can be computed efficiently for distributions in the exponential family and decreases like 1/N during learning. We apply the surprise framework to predict human gaze shifts under natural conditions. Humans are strongly attracted to locations of high Bayesian surprise, with 72% of all human gaze shifts directed towards locations more surprising than the average, a figure which rises to 84% when considering gaze targets simultaneously selected by multiple observers. The theory of surprise is applicable across different spatio-temporal scales, modalities, and levels of abstraction.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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