Beyond Black Box Densities: Parameter Learning for the Deviated Components

Neural Information Processing Systems 

As we collect additional samples from a data population for which a known density function estimate may have been previously obtained by a black box method, the increased complexity of the data set may result in the true density being deviated from the known estimate by a mixture distribution.

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