Distance metric learning based on structural neighborhoods for dimensionality reduction and classification performance improvement

Distance metric learning can be viewed as one of the fundamental interests in pattern recognition and machine learning, which plays a pivotal role in the performance of many learning methods. One of the effective methods in learning such a metric is to learn it from a set of labeled training samples... (read more)

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