| Document Date: 2014-11-05 12:24:13
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Company Baidu / Amazon / Yahoo!LDA / Google / Facebook / ProxU / Apache Software Foundation / Yahoo / Microsoft / / Country Jordan / / / Facility Carnegie Mellon University / / Holiday Assumption / / IndustryTerm stale synchronous parallel parameter server / machine learning algorithms / distributed machine learning algorithms / online advertising / simplified data processing / asynchronous algorithms / proximal algorithms / data mining / parameter server / distributed optimization algorithms / similar algorithm / distributed subgradient algorithm / proximal gradient algorithms / distributed subgradient descent algorithm / server / internet applications / proximal operator / inference algorithm / optimization algorithms / realistic industrial machine learning applications / ter server / large Internet / worker groups / big data systems / generalized proximal operator / machine learning applications / social network / large-scale peer-to-peer systems / / NaturalFeature Mt Lvar / / Organization Apache Foundation / Carnegie Mellon University / / Person A. Talwalkar / V / A. Ng / K. Yang / David G. Andersen / S. Narayanamurthy / V / P. Tucker / Alexander Smola / A. Amhed / V / Kai Yu / / Position Prime Minister / servers worker / wb / algorithm designer / author / average worker / tackle / server worker / scheduler / particular worker / workers Worker / / Product parame10 Parameter server / Franklin / parame10 Parameter / / PublishedMedium Machine Learning / / Technology machine learning algorithms / Peer-to-peer / distributed subgradient algorithm / API / distributed machine learning algorithms / inference algorithm / underlying algorithms / distributed subgradient descent algorithm / Machine Learning / shared memory / proximal gradient algorithms / Ethernet / load balancing / proposed algorithm / optimization algorithms / similar algorithm / distributed optimization algorithms / data mining / caching / 3 Algorithm / Sequential Consistency / same algorithm / 5 Algorithm / / URL http /
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Communication Efficient Distributed Machine Learning with the Parameter Server Mu Li∗† , David G. Andersen∗ , Alexander Smola∗‡ , and Kai Yu† ∗ Carnegie Mellon University † Baidu ‡ Google