898 citations · 1.2k across the 19 of their papers we have counts for
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cs.LG2017★ 2 cited
Efficient Use of Limited-Memory Accelerators for Linear Learning on Heterogeneous Systems
Celestine Dünner, Thomas Parnell, Martin Jaggi
We propose a generic algorithmic building block to accelerate training of machine learning models on heterogeneous compute systems. Our scheme allows to efficiently employ compute…
cs.LG2017
Large-Scale Stochastic Learning using GPUs
Thomas Parnell, Celestine Dünner, Kubilay Atasu +2
In this work we propose an accelerated stochastic learning system for very large-scale applications. Acceleration is achieved by mapping the training algorithm onto massively paral…