Most studies in statistical or machine learning based authorship attribution focus on two or a few authors. This leads to an overestimation of the importance of the features extra...
This paper presents various strategies for improving the extraction performance of less prominent relations with the help of the rules learned for similar relations, for which lar...
Many numerical algorithms are specified in terms of operations on vectors and matrices. Matrix operations can be executed extremely efficiently using specialized linear algebra k...
Some of the most successful recent applications of reinforcement learning have used neural networks and the TD algorithm to learn evaluation functions. In this paper, we examine t...
Recently, many advanced machine learning approaches have been proposed for coreference resolution; however, all of the discriminatively-trained models reason over mentions rather ...
Michael L. Wick, Aron Culotta, Khashayar Rohaniman...