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...
We describe a single convolutional neural network architecture that, given a sentence, outputs a host of language processing predictions: part-of-speech tags, chunks, named entity...
Abstract. We present the Operator Language (OL), a framework to automatically generate fast numerical kernels. OL provides the structure to extend the program generation system Spi...
This paper introduces a new kernel which computes similarity between two natural language sentences as the number of paths shared by their dependency trees. The paper gives a very...