Papers › Kernel Conditional Exponential Family

Kernel Conditional Exponential Family

15 Nov 2017arXiv:1711.05363archive 2025-07-28

Michael Arbel, Arthur Gretton

A nonparametric family of conditional distributions is introduced, which generalizes conditional exponential families using functional parameters in a suitable RKHS. An algorithm is provided for learning the generalized natural parameter, and consistency of the estimator is established in the well specified case. In experiments, the new method generally outperforms a competing approach with consistency guarantees, and is competitive with a deep conditional density model on datasets that exhibit abrupt transitions and heteroscedasticity.

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