Use of Code Structural Features for Machine Learning to Predict Effective Optimizations - researchr publication authors

researchr

You are not signed in
Sign in
Sign up

Yuki Kawarabatake, Mulya Agung, Kazuhiko Komatsu, Ryusuke Egawa, Hiroyuki Takizawa. Use of Code Structural Features for Machine Learning to Predict Effective Optimizations. In 2018 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPS Workshops 2018, Vancouver, BC, Canada, May 21-25, 2018. pages 1049-1055, IEEE Computer Society, 2018. [doi]

This author has not been identified. Look up 'Yuki Kawarabatake' in GoogleThis author has not been identified. Look up 'Mulya Agung' in GoogleThis author has not been identified. Look up 'Kazuhiko Komatsu' in GoogleThis author has not been identified. Look up 'Ryusuke Egawa' in GoogleThis author has not been identified. Look up 'Hiroyuki Takizawa' in Google

runs on WebDSL