Kernelized sorting is an approach for matching objects from two sources (or domains) that does not require any prior notion of similarity between objects across the two sources. U...
Jagadeesh Jagarlamudi, Seth Juarez, Hal Daum&eacut...
Convolution kernels, such as sequence and tree kernels, are advantageous for both the concept and accuracy of many natural language processing (NLP) tasks. Experiments have, howev...
In recent years tree kernels have been proposed for the automatic learning of natural language applications. Unfortunately, they show (a) an inherent super linear complexity and (...
This paper devises a novel kernel function for structured natural language data. In the field of Natural Language Processing, feature extraction consists of the following two ste...