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Revisiting Distributed Synchronous SGD

Mar 21, 2017
Jianmin Chen, Xinghao Pan, Rajat Monga, Samy Bengio, Rafal Jozefowicz

* 10 pages 

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Hemingway: Modeling Distributed Optimization Algorithms

Feb 20, 2017
Xinghao Pan, Shivaram Venkataraman, Zizheng Tai, Joseph Gonzalez

* Presented at ML Systems Workshop at NIPS, Dec 2016 

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CYCLADES: Conflict-free Asynchronous Machine Learning

May 31, 2016
Xinghao Pan, Maximilian Lam, Stephen Tu, Dimitris Papailiopoulos, Ce Zhang, Michael I. Jordan, Kannan Ramchandran, Chris Re, Benjamin Recht

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Perturbed Iterate Analysis for Asynchronous Stochastic Optimization

Mar 25, 2016
Horia Mania, Xinghao Pan, Dimitris Papailiopoulos, Benjamin Recht, Kannan Ramchandran, Michael I. Jordan

* 30 pages 

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Parallel Correlation Clustering on Big Graphs

Jul 20, 2015
Xinghao Pan, Dimitris Papailiopoulos, Samet Oymak, Benjamin Recht, Kannan Ramchandran, Michael I. Jordan

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MLI: An API for Distributed Machine Learning

Oct 25, 2013
Evan R. Sparks, Ameet Talwalkar, Virginia Smith, Jey Kottalam, Xinghao Pan, Joseph Gonzalez, Michael J. Franklin, Michael I. Jordan, Tim Kraska

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Optimistic Concurrency Control for Distributed Unsupervised Learning

Jul 30, 2013
Xinghao Pan, Joseph E. Gonzalez, Stefanie Jegelka, Tamara Broderick, Michael I. Jordan

* 25 pages, 5 figures 

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Conditions for Convergence in Regularized Machine Learning Objectives

May 17, 2013
Patrick Hop, Xinghao Pan

* 3 Pages 

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