Online Metric Learning and Fast Similarity Search

  title={Online Metric Learning and Fast Similarity Search},
  author={Prateek Jain and Brian Kulis and Inderjit S. Dhillon and Kristen Grauman},
Metric learning algorithms can provide useful distance functions for a variety of domains, and recent work has shown good accuracy for problems where the learner can access all distance constraints at once. However, in many real applications, constraints are only available incrementally, thus necessitating methods that can perform online updates to the learned metric. Existing online algorithms offer bounds on worst-case performance, but typically do not perform well in practice as compared to… CONTINUE READING
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