An algorithm directly finding the K most probable configurations in Bayesian networks
نویسندگان
چکیده
منابع مشابه
Finding the M Most Probable Configurations using Loopy Belief Propagation
Loopy belief propagation (BP) has been successfully used in a number of difficult graphical models to find the most probable configuration of the hidden variables. In applications ranging from protein folding to image analysis one would like to find not just the best configuration but rather the top M . While this problem has been solved using the junction tree formalism, in many real world pro...
متن کاملStudy of the Most Probable Explanation in Hybrid Bayesian Networks
In addition to computing the posterior distributions for hidden variables in Bayesian networks, one other important inference task is to find the most probable explanation (MPE). MPE provides the most likely configurations to explain away the evidence and helps to manage hypotheses for decision making. In recent years, researchers have proposed a few methods to find the MPE for discrete Bayesia...
متن کاملStructure Approximation of Most Probable Explanations in Bayesian Networks
Abstract Typically, when one discusses approximation algorithms for (NP-hard) problems (like TRAVELING SALESPERSON, VERTEX COVER, KNAPSACK), one refers to algorithms that return a solution whose value is (at least ideally) close to optimal; e.g., a tour with almost minimal length, a vertex cover of size just above minimal, or collection of objects that has close to maximal value. In contrast, o...
متن کاملMost probable explanations in Bayesian networks: Complexity and tractability
An overview is given of definitions and complexity results of a number of variants of the problem of probabilistic inference of the most probable explanation of a set of hypotheses given observed phenomena.
متن کاملAn efficient algorithm for finding the M most probable configurationsin probabilistic expert systems
A probabilistic expert system provides a graphical representation of a joint probability distribution which enables local computations of probabilities. Dawid (1992) provided a ‘flow-propagation’ algorithm for finding the most probable configuration of the joint distribution in such a system. This paper analyses that algorithm in detail, and shows how it can be combined with a clever partitioni...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Approximate Reasoning
سال: 1994
ISSN: 0888-613X
DOI: 10.1016/0888-613x(94)90031-0