  We aim to analyze the relation between two random vectors that may
potentially have both different number of attributes as well as realizations,
and which may even not have a joint distribution. This problem arises in many
practical domains, including biology and architecture. Existing techniques
assume the vectors to have the same domain or to be jointly distributed, and
hence are not applicable. To address this, we propose Canonical Divergence
Analysis (CDA). We introduce three instantiations, each of which permits
practical implementation. Extensive empirical evaluation shows the potential of
our method.
