Irregular and sparse scientific computing programs frequently experience performance losses due to inefficient use of the memory system in most machines. Previous work has shown t...
Michelle Mills Strout, Nissa Osheim, Dave Rostron,...
The field of information retrieval still strives to develop models which allow semantic information to be integrated in the ranking process to improve performance in comparison to...
We describe a new sketch recognition framework for chemical structure drawings that combines multiple levels of visual features using a jointly trained conditional random field. ...
Abstract. This paper presents PerWiz, a performance prediction tool for improving the performance of message passing programs. PerWiz focuses on locating where a significant impro...
We address the problem of extracting bilingual chunk pairs from parallel text to create training sets for statistical machine translation. We formulate the problem in terms of a s...