Bayesian Active Distance Metric Learning

Understand

Distance metric learning is an important component for many tasks, such as statistical classification and content-based image retrieval.

• Existing approaches for learning distance metrics from pairwise constraints typically suffer from two major problems.
• First, most algorithms only offer point estimation of the distance metric and can therefore be unreliable when the number of training examples is small.
• Second, since these algorithms generally select their training examples at random, they can be inefficient if labeling effort is limited.