Definition: In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.
Input: This paper describes a class of probabilistic approximation algorithms based on bucket elimination which offer adjustable levels of accuracy and efficiency. We analyze the ap­ proximation for several tasks: finding the most probable explanation, belief updat­ ing and finding the maximum a posteriori hypothesis. We identify regions of com­ pleteness and provide preliminary empiri­ cal evaluation on randomly generated net­

A scheme for approximating probabilistic inference