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Parallel training of linear models without compromising convergence

Nov 05, 2018
Nikolas Ioannou, Celestine Dünner, Kornilios Kourtis, Thomas Parnell

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A Distributed Second-Order Algorithm You Can Trust

Jun 20, 2018
Celestine Dünner, Aurelien Lucchi, Matilde Gargiani, An Bian, Thomas Hofmann, Martin Jaggi

* appearing at ICML 2018 - Proceedings of the 35th International Conference on Machine Learning, Stockholm, Schweden, PMLR 80, 2018 

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Snap ML: A Hierarchical Framework for Machine Learning

Jun 18, 2018
Celestine Dünner, Thomas Parnell, Dimitrios Sarigiannis, Nikolas Ioannou, Andreea Anghel, Haralampos Pozidis

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Understanding and Optimizing the Performance of Distributed Machine Learning Applications on Apache Spark

Dec 13, 2017
Celestine Dünner, Thomas Parnell, Kubilay Atasu, Manolis Sifalakis, Haralampos Pozidis

* To appear in the 2017 IEEE International Conference on Big Data (Big Data 2017), December 11-14, 2017, Boston, MA, USA 

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Efficient Use of Limited-Memory Accelerators for Linear Learning on Heterogeneous Systems

Nov 07, 2017
Celestine Dünner, Thomas Parnell, Martin Jaggi

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Large-Scale Stochastic Learning using GPUs

Feb 22, 2017
Thomas Parnell, Celestine Dünner, Kubilay Atasu, Manolis Sifalakis, Haris Pozidis

* Accepted for publication in ParLearning 2017: The 6th International Workshop on Parallel and Distributed Computing for Large Scale Machine Learning and Big Data Analytics, Orlando, Florida, May 2017 

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Primal-Dual Rates and Certificates

Jun 02, 2016
Celestine Dünner, Simone Forte, Martin Takáč, Martin Jaggi

* appearing at ICML 2016 - Proceedings of the 33rd International Conference on Machine Learning, New York, NY, USA, 2016. JMLR: W&CP volume 48 

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