Label Ranking under Ambiguous Supervision for Learning Semantic Correspondences

@inproceedings{Bordes2010LabelRU,
  title={Label Ranking under Ambiguous Supervision for Learning Semantic Correspondences},
  author={Antoine Bordes and Nicolas Usunier and Jason Weston},
  booktitle={ICML},
  year={2010}
}
This paper studies the problem of learning from ambiguous supervision, focusing on the task of learning semantic correspondences. A learning problem is said to be ambiguously supervised when, for a given training input, a set of output candidates is provided with no prior of which one is correct. We propose to tackle this problem by solving a related unambiguous task with a label ranking approach and show how and why this performs well on the original task, via the method of task-transfer. We… CONTINUE READING

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