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dc.contributor.advisorTomaso Poggio
dc.contributor.authorCaponnetto, Andreaen_US
dc.contributor.authorPoggio, Tomasoen_US
dc.contributor.authorBouvrie, Jakeen_US
dc.contributor.authorRosasco, Lorenzoen_US
dc.contributor.authorSmale, Steveen_US
dc.contributor.otherCenter for Biological and Computational Learning (CBCL)en_US
dc.date.accessioned2008-11-27T01:30:05Z
dc.date.available2008-11-27T01:30:05Z
dc.date.issued2008-11-26
dc.identifier.urihttp://hdl.handle.net/1721.1/43713
dc.description.abstractWe propose a natural image representation, the neural response, motivated by the neuroscience of the visual cortex. The inner product defined by the neural response leads to a similarity measure between functions which we call the derived kernel. Based on a hierarchical architecture, we give a recursive definition of the neural response and associated derived kernel. The derived kernel can be used in a variety of application domains such as classification of images, strings of text and genomics data.en_US
dc.format.extent25 p.en_US
dc.relation.ispartofseriesMIT-CSAIL-TR-2008-070
dc.relation.ispartofseriesCBCL-276
dc.subjectneuroscienceen_US
dc.subjectcomputer visionen_US
dc.subjectkernelsen_US
dc.titleMathematics of the Neural Responseen_US


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