Given the task definition, example input & output, solve the new input case.
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.
Example: We propose a local coherence model based on a convolutional neural network that operates over the entity grid representation of a text. The model captures long range entity transitions along with entity-specific features without loosing generalization, thanks to the power of distributed representation. We present a pairwise ranking method to train the model in an end-to-end fashion on a task and learn task-specific high level features. Our evaluation on three different coherence assessment tasks demonstrates that our model achieves state of the art results outperforming existing models by a good margin.
Output: A Neural Local Coherence Model
This statement "A Neural Local Coherence Model" is taken from the subtext "convolutional neural network" and its explanation in the passage. This is a positive example because the title belongs to the mentions in the passage

New input case for you: P lanning problems where effects of actions are non-deterministic can be modeled a8 Markov decision processes. Planning prob lems are usually goal-directed. This paper proposes several techniques for exploiting the goal-directedness to accelerate value itera tion, a standard algorithm for solving Markov decision processes. Empirical studies have shown that the techniques can bring about significant speedups.
Output:
Fast Value Iteration for Goal-Directed Markov Decision Processes