Scipediacontent: Scipediacontent moved page Draft Content 426053024 to Recht et al 2016a

2021-02-02T06:43:15Z

Scipediacontent moved page Draft Content 426053024 to Recht et al 2016a

Scipediacontent: Created page with " == Abstract == Modern advanced analytics applications make use of machine learning techniques and contain multiple steps of domain-specific and general-purpose processing wi..."

2021-02-02T06:43:11Z

Created page with " == Abstract == Modern advanced analytics applications make use of machine learning techniques and contain multiple steps of domain-specific and general-purpose processing wi..."

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== Abstract ==

Modern advanced analytics applications make use of machine learning techniques and contain multiple steps of domain-specific and general-purpose processing with high resource requirements. We present KeystoneML, a system that captures and optimizes the end-to-end large-scale machine learning applications for high-throughput training in a distributed environment with a high-level API. This approach offers increased ease of use and higher performance over existing systems for large scale learning. We demonstrate the effectiveness of KeystoneML in achieving high quality statistical accuracy and scalable training using real world datasets in several domains. By optimizing execution KeystoneML achieves up to 15x training throughput over unoptimized execution on a real image classification application.

== Original document ==

The different versions of the original document can be found in:

* [http://arxiv.org/abs/1610.09451 http://arxiv.org/abs/1610.09451]

* [http://arxiv.org/pdf/1610.09451 http://arxiv.org/pdf/1610.09451]

* [http://dx.doi.org/10.1109/icde.2017.109 http://dx.doi.org/10.1109/icde.2017.109]

* [http://xplorestaging.ieee.org/ielx7/7929494/7929895/07930005.pdf?arnumber=7930005 http://xplorestaging.ieee.org/ielx7/7929494/7929895/07930005.pdf?arnumber=7930005],
: [http://dx.doi.org/10.1109/icde.2017.109 http://dx.doi.org/10.1109/icde.2017.109]

* [https://dblp.uni-trier.de/db/journals/corr/corr1610.html#SparksVKFR16 https://dblp.uni-trier.de/db/journals/corr/corr1610.html#SparksVKFR16],
: [https://arxiv.org/abs/1610.09451 https://arxiv.org/abs/1610.09451],
: [https://ui.adsabs.harvard.edu/abs/2016arXiv161009451S/abstract https://ui.adsabs.harvard.edu/abs/2016arXiv161009451S/abstract],
: [https://ieeexplore.ieee.org/document/7930005 https://ieeexplore.ieee.org/document/7930005],
: [http://dblp.uni-trier.de/db/journals/corr/corr1610.html#SparksVKFR16 http://dblp.uni-trier.de/db/journals/corr/corr1610.html#SparksVKFR16],
: [http://ieeexplore.ieee.org/document/7930005 http://ieeexplore.ieee.org/document/7930005],
: [https://doi.org/10.1109/ICDE.2017.109 https://doi.org/10.1109/ICDE.2017.109],
: [https://dissem.in/p/83374154/keystoneml-optimizing-pipelines-for-large-scale-advanced-analytics https://dissem.in/p/83374154/keystoneml-optimizing-pipelines-for-large-scale-advanced-analytics],
: [https://academic.microsoft.com/#/detail/2547386789 https://academic.microsoft.com/#/detail/2547386789]

← Older revision	Revision as of 06:43, 2 February 2021
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Recht et al 2016a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 426053024 to Recht et al 2016a

Scipediacontent: Created page with " == Abstract == Modern advanced analytics applications make use of machine learning techniques and contain multiple steps of domain-specific and general-purpose processing wi..."