Learning the Information Divergence

5 Jun 2014Onur DikmenZhirong YangErkki Oja

Information divergence that measures the difference between two nonnegative matrices or tensors has found its use in a variety of machine learning problems. Examples are Nonnegative Matrix/Tensor Factorization, Stochastic Neighbor Embedding, topic models, and Bayesian network optimization... (read more)

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