WSABIE: Scaling Up to Large Vocabulary Image Annotation

@inproceedings{Weston2011WSABIESU,
  title={WSABIE: Scaling Up to Large Vocabulary Image Annotation},
  author={Jason Weston and Samy Bengio and Nicolas Usunier},
  booktitle={IJCAI},
  year={2011}
}
Image annotation datasets are becoming larger and larger, with tens of millions of images and tens of thousands of possible annotations. We propose a strongly performing method that scales to such datasets by simultaneously learning to optimize precision at the top of the ranked list of annotations for a given image and learning a lowdimensional joint embedding space for both images and annotations. Our method, called WSABIE, both outperforms several baseline methods and is faster and consumes… CONTINUE READING

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