Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD - researchr publication authors

researchr

You are not signed in
Sign in
Sign up

Sanghamitra Dutta, Gauri Joshi, Soumyadip Ghosh, Parijat Dube, Priya Nagpurkar. Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD. In Amos J. Storkey, Fernando Pérez-Cruz, editors, International Conference on Artificial Intelligence and Statistics, AISTATS 2018, 9-11 April 2018, Playa Blanca, Lanzarote, Canary Islands, Spain. Volume 84 of Proceedings of Machine Learning Research, pages 803-812, PMLR, 2018. [doi]

This author has not been identified. Look up 'Sanghamitra Dutta' in GoogleThis author has not been identified. Look up 'Gauri Joshi' in GoogleThis author has not been identified. Look up 'Soumyadip Ghosh' in GoogleThis author has not been identified. Look up 'Parijat Dube' in GoogleThis author has not been identified. Look up 'Priya Nagpurkar' in Google

runs on WebDSL