The application of statistical methods to natural language processing has been remarkably successful over the past two decades. But, to deal with recent problems arising in this ...
Abstract— The paper presents an efficient construction algorithm for obtaining sparse kernel density estimates based on a regression approach that directly optimizes model gener...
In this paper, we propose a machine learning algorithm for shallow semantic parsing, extending the work of Gildea and Jurafsky (2002), Surdeanu et al. (2003) and others. Our algor...
Sameer Pradhan, Wayne Ward, Kadri Hacioglu, James ...
This paper presents a decomposition method for efficiently constructing 1-norm Support Vector Machines (SVMs). The decomposition algorithm introduced in this paper possesses many d...
We describe an algorithm for converting linear support vector machines and any other arbitrary hyperplane-based linear classifiers into a set of non-overlapping rules that, unlike...