Deep Divergence Learning

no code implementations • ICML 2020 • Kubra Cilingir, Rachel Manzelli, Brian Kulis

Classical linear metric learning methods have recently been extended along two distinct lines: deep metric learning methods for learning embeddings of the data using neural networks, and Bregman divergence learning approaches for extending learning Euclidean distances to more general divergence measures such as divergences over distributions.

Clustering Metric Learning