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: Consider Input: The deep Boltzmann machine (DBM) has been an important development in the quest for powerful "deep" probabilistic models. To date, simultaneous or joint training of all layers of the DBM has been largely unsuccessful with existing training methods. We introduce a simple regularization scheme that encourages the weight vectors associated with each hidden unit to have similar norms. We demonstrate that this regularization can be easily combined with standard stochastic maximum likelihood to yield an effective training strategy for the simultaneous training of all layers of the deep Boltzmann machine.

Output: On Training Deep Boltzmann Machines

Input: Consider Input: Automated Essay Scoring (AES) has been quite popular and is being widely used. However, lack of appropriate methodology for rating nonnative English speakers' essays has meant a lopsided advancement in this field. In this paper, we report initial results of our experiments with nonnative AES that learns from manual evaluation of nonnative essays. For this purpose, we conducted an exercise in which essays written by nonnative English speakers in test environment were rated both manually and by the automated system designed for the experiment. In the process, we experimented with a few features to learn about nuances linked to nonnative evaluation. The proposed methodology of automated essay evaluation has yielded a correlation coefficient of 0.750 with the manual evaluation.

Output: Exploring Automated Essay Scoring for Nonnative English Speakers

Input: Consider Input: In situ hybridisation gene expression information helps biologists identify where a gene is expressed. However, the databases that republish the experimental information are often both incomplete and inconsistent. This paper examines a system, Argudas, designed to help tackle these issues. Argudas is an evolution of an existing system, and so that system is reviewed as a means of both explaining and justifying the behaviour of Argudas. Throughout the discussion of Argudas a number of issues will be raised including the appropriateness of argumentation in biology and the challenges faced when integrating apparently similar online biological databases.
Output: Argudas: arguing with gene expression information