  This paper considers derivation of $f$-divergence inequalities via the
approach of functional domination. Bounds on an $f$-divergence based on one or
several other $f$-divergences are introduced, dealing with pairs of probability
measures defined on arbitrary alphabets. In addition, a variety of bounds are
shown to hold under boundedness assumptions on the relative information. The
journal paper, which includes more approaches for the derivation of
f-divergence inequalities and proofs, is available on the arXiv at
https://arxiv.org/abs/1508.00335, and it has been published in the IEEE Trans.
on Information Theory, vol. 62, no. 11, pp. 5973-6006, November 2016.
