… When the marginal probability inference is tractable, standard combinatorial search … In this
paper, we present a new anytime algorithm to perform marginal MAP inference in graphical …

… -first search solvers into anytime schemes. The weighted best-… fective anytime behavior for
pure MAP tasks, Marginal MAP is … effective anytime solvers for Marginal MAP yielding the most …

… We introduce new anytime search algorithms that combine best-first with depth-first search
into hybrid schemes for Marginal MAP inference in graphical models. The main goal is to …

… Marginal MAP inference task is known to be extremely hard particularly because the evaluation
of each complete MAP … solvers that focus on computing anytime upper and lower bounds …

… Marginal MAP is a key task in Bayesian inference and … the evaluation of each MAP assignment
requires solving an … that provides anytime upper bounds for marginal MAP in graphical …

… good anytime behavior and the high cost of evaluating a MAP … These algorithms demonstrate
significantly better anytime … To understand A*’s performance for marginal MAP inference, …

… Continuing in the same vein as the previous experiments, we apply our method for MAP and
marginal MAP inference on larger graphs that contain cycles. We consider MMAP problems …

… sum inference task, which includes marginal MAP, along with pure marginalization and … is
sufficiently general to be applied easily to marginal MAP. (2) Any-time: it yields a bound at any …

… a distributed anytime algorithm for performing MAP inference in … MAP inference. It extends
MPLP by iteratively adding clusters to the MPLP formulation thus approximating the marginal …

… Marginal MAP is a difficult mixed inference task for graphical … solution value in an anytime
fashion. These methods however are … limited memory and computes anytime upper and lower …