A visual representation of the parametrization of the augmented Vajda's lower bound. As we can see, it is symmetric around the augmented KL divergence axis.
Abstract:
We provide optimal lower and upper bounds for the augmented Kullback-Leibler divergence in terms of the augmented total variation distance between two probability measure...Show MoreMetadata
Abstract:
We provide optimal lower and upper bounds for the augmented Kullback-Leibler divergence in terms of the augmented total variation distance between two probability measures defined on two Euclidean spaces having different dimensions. We call them refined Pinsker’s and reverse Pinsker’s inequalities, respectively.
A visual representation of the parametrization of the augmented Vajda's lower bound. As we can see, it is symmetric around the augmented KL divergence axis.
Published in: IEEE Access ( Volume: 10)
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