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Publication Detail
Spread divergence
  • Publication Type:
  • Authors:
    Zhang M, Hayes P, Bird T, Habib R, Barber D
  • Publication date:
  • Pagination:
    11040, 11050
  • Published proceedings:
    37th International Conference on Machine Learning, ICML 2020
  • Volume:
  • ISBN-13:
  • Status:
For distributions P and Q with different supports or undefined densities, the divergence D(PjjQ) may not exist. We define a Spread Divergence D(PjjQ) on modified P and Q and describe sufficient conditions for the existence of such a divergence. We demonstrate how to maximize the discriminatory power of a given divergence by parameterizing and learning the spread. We also give examples of using a Spread Divergence to train implicit generative models, including linear models (Independent Components Analysis) and non-linear models (Deep Generative Networks).
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