"A related idea, reference priors, was introduced by Jose M. Bernardo. Here, the idea is to maximize the expected Kullback-Leibler divergence of the posterior distribution relative to the prior. This maximizes the expected posterior information about x when the prior density is p(x). The reference prior is defined in the asymptotic limit, i.e., one considers the limit of the priors so obtained as the number of data points goes to infinity. Reference priors are often the objective prior of choice in multivariate problems, since other rules (e.g., Jeffreys' rule) may result in priors with problematic behavior."
Prior probability - Wikipedia
"In the above we have used the word reference prior. In general we mean by this a prior which it is convenient to use as a standard. In principle, a reference prior might or might not be dominated by the likelihood, but in this book reference priors which are diminated by the likelihood are often employed."
Box and Tiao, 1973