2012 RandomForestsforMetricLearningw

• (Xiong et al., 2012) ⇒ Caiming Xiong, David Johnson, Ran Xu, and Jason J. Corso. (2012). “Random Forests for Metric Learning with Implicit Pairwise Position Dependence.” In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2012). ISBN:978-1-4503-1462-6 doi:10.1145/2339530.2339680

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%222012%22+Random+Forests+for+Metric+Learning+with+Implicit+Pairwise+Position+Dependence
• http://dl.acm.org/citation.cfm?id=2339530.2339680&preflayout=flat#citedby

Quotes

Author Keywords

• Data mining; metric learning; pairwise constraints; random forests; statistical; structural

Abstract

Metric learning makes it plausible to learn semantically meaningful distances for complex distributions of data using label or pairwise constraint information. However, to date, most metric learning methods are based on a single Mahalanobis metric, which cannot handle heterogeneous data well. Those that learn multiple metrics throughout the feature space have demonstrated superior accuracy, but at a severe cost to computational efficiency. Here, we adopt a new angle on the metric learning problem and learn a single metric that is able to implicitly adapt its distance function throughout the feature space. This metric adaptation is accomplished by using a random forest-based classifier to underpin the distance function and incorporate both absolute pairwise position and standard relative position into the representation. We have implemented and tested our method against state of the art global and multi-metric methods on a variety of data sets. Overall, the proposed method outperforms both types of method in terms of accuracy (consistently ranked first) and is an order of magnitude faster than state of the art multi-metric methods (16x faster in the worst case).

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2012 RandomForestsforMetricLearningw	Caiming Xiong David Johnson Ran Xu Jason J. Corso			Random Forests for Metric Learning with Implicit Pairwise Position Dependence				10.1145/2339530.2339680		2012