Discriminative and consistent similarities in instance-level Multiple Instance Learning
@article{Rastegari2015DiscriminativeAC, title={Discriminative and consistent similarities in instance-level Multiple Instance Learning}, author={Mohammad Rastegari and Hannaneh Hajishirzi and Ali Farhadi}, journal={2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year={2015}, pages={740-748} }
In this paper we present a bottom-up method to instance-level Multiple Instance Learning (MIL) that learns to discover positive instances with globally constrained reasoning about local pairwise similarities. We discover positive instances by optimizing for a ranking such that positive (top rank) instances are highly and consistently similar to each other and dissimilar to negative instances. Our approach takes advantage of a discriminative notion of pairwise similarity coupled with a…
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