  With similarity-based content delivery, the request for a content can be
satisfied by delivering a related content under a dissimilarity cost. This
letter addresses the joint optimization of caching and similarity-based
delivery decisions across a network so as to minimize the weighted sum of
average delay and dissimilarity cost. A convergent alternate gradient descent
ascent algorithm is first introduced for an offline scenario with prior
knowledge of the request rates, and then extended to an online setting.
Numerical results validate the advantages of the approach with respect to
standard per-cache solutions.
