Andrew Latham

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We study the problem of bag-level classification from generalized multiple-instance (GMI) data. GMI learning is an extension of the popular multiple-instance setting. In GMI data, bags are labeled positive if they contain instances of certain types, and avoid instances of other types. For example , an image of a " sunny beach " should contain sand and sea,(More)
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