Petuum: A new platform for distributed machine learning on big data
How can one build a distributed framework that allows efficient deployment of a wide
spectrum of modern advanced machine learning (ML) programs for industrial-scale …
spectrum of modern advanced machine learning (ML) programs for industrial-scale …
[PDF][PDF] Petuum: A New Platform for Distributed Machine Learning on Big Data
EP Xing, Q Ho, W Dai, JK Kim, J Wei, S Lee, X Zheng… - stat, 2015 - cobweb.cs.uga.edu
What is a systematic way to efficiently apply a wide spectrum of advanced ML programs to
industrial scale problems, using Big Models (up to 100s of billions of parameters) on Big …
industrial scale problems, using Big Models (up to 100s of billions of parameters) on Big …
[PDF][PDF] Petuum: A New Platform for Distributed Machine Learning on Big Data
EP Xing, Q Ho, W Dai, JK Kim, J Wei, S Lee, X Zheng… - opro.ai
What is a systematic way to efficiently apply a wide spectrum of advanced ML programs to
industrial scale problems, using Big Models (up to 100s of billions of parameters) on Big …
industrial scale problems, using Big Models (up to 100s of billions of parameters) on Big …
Petuum: A New Platform for Distributed Machine Learning on Big Data
EP Xing, Q Ho, W Dai, JK Kim, J Wei, S Lee… - IEEE Transactions on …, 2015 - computer.org
What is a systematic way to efficiently apply a wide spectrum of advanced ML programs to
industrial scale problems, using Big Models (up to 100 s of billions of parameters) on Big …
industrial scale problems, using Big Models (up to 100 s of billions of parameters) on Big …
[PDF][PDF] Petuum: A New Platform for Distributed Machine Learning on Big Data
EP Xing, Q Ho, W Dai, JK Kim, J Wei, S Lee, X Zheng… - Citeseer
What is a systematic way to efficiently apply a wide spectrum of advanced ML programs to
industrial scale problems, using Big Models (up to 100 s of billions of parameters) on Big …
industrial scale problems, using Big Models (up to 100 s of billions of parameters) on Big …
[PDF][PDF] Petuum: A New Platform for Distributed Machine Learning on Big Data
EP Xing, Q Ho, W Dai, JK Kim, J Wei, S Lee, X Zheng… - stat, 2015 - academia.edu
What is a systematic way to efficiently apply a wide spectrum of advanced ML programs to
industrial scale problems, using Big Models (up to 100s of billions of parameters) on Big …
industrial scale problems, using Big Models (up to 100s of billions of parameters) on Big …
[PDF][PDF] Petuum: A New Platform for Distributed Machine Learning on Big Data
EP Xing, Q Ho, W Dai, JK Kim, J Wei, S Lee, X Zheng… - scholar.archive.org
What is a systematic way to efficiently apply a wide spectrum of advanced ML programs to
industrial scale problems, using Big Models (up to 100 s of billions of parameters) on Big …
industrial scale problems, using Big Models (up to 100 s of billions of parameters) on Big …
[PDF][PDF] Petuum: A New Platform for Distributed Machine Learning on Big Data
EP Xing, Q Ho, W Dai, JK Kim, J Wei, S Lee, X Zheng… - cs.uwaterloo.ca
What is a systematic way to efficiently apply a wide spectrum of advanced ML programs to
industrial scale problems, using Big Models (up to 100 s of billions of parameters) on Big …
industrial scale problems, using Big Models (up to 100 s of billions of parameters) on Big …
Petuum: A New Platform for Distributed Machine Learning on Big Data
EP Xing, Q Ho, W Dai, JK Kim, J Wei, S Lee… - arXiv e …, 2013 - ui.adsabs.harvard.edu
What is a systematic way to efficiently apply a wide spectrum of advanced ML programs to
industrial scale problems, using Big Models (up to 100s of billions of parameters) on Big …
industrial scale problems, using Big Models (up to 100s of billions of parameters) on Big …
Petuum: A New Platform for Distributed Machine Learning on Big Data
EP Xing, Q Ho, W Dai, JK Kim, J Wei, S Lee… - arXiv preprint arXiv …, 2013 - arxiv.org
What is a systematic way to efficiently apply a wide spectrum of advanced ML programs to
industrial scale problems, using Big Models (up to 100s of billions of parameters) on Big …
industrial scale problems, using Big Models (up to 100s of billions of parameters) on Big …