Conjugate Generalized Bayesian Inference for Discrete Doubly Intractable Problems
离散双重难解问题的共轭广义贝叶斯推断
Doubly intractable problems occur when both the likelihood and the posterior are available only in unnormalized form, with computationally intractable normalization constants. Bayesian inference then typically requires direct approximation of the posterior through specialized and typically expensive MCMC methods. In this paper, we provide a computationally efficient alternative in the form of a novel generalized Bayesian posterior that allows for conjugate, closed-form or…