We propose a general framework for constructing universal steering criteria
that are applicable to arbitrary bipartite states and measurement settings of
the steering party. The same framework is also useful for studying the joint
measurement problem. Based on the data-processing inequality for an extended
R\'enyi relative entropy, we then introduce a family of universal steering
inequalities, which detect steering much more efficiently than those
inequalities known before. As illustrations, we show unbounded violation of a
steering inequality for assemblages constructed from mutually unbiased bases
and establish an interesting connection between maximally steerable assemblages
and complete sets of mutually unbiased bases. We also provide a single steering
inequality that can detect all bipartite pure states of full Schmidt rank. In
the course of study, we generalize a number of results intimately connected to
data-processing inequalities, which are of independent interest.Comment: 5+6 pages, two figures, comments and suggestions are very welcome