Fast On-line Statistical Learning on a GPGPU
On-line Machine Learning using Stochastic Gradient Descent is an inherently sequential computation. This makes it difficult to improve performance by simply employing parallel architectures. Langford et al. made a modification to the standard stochastic gradient descent approach which opens up the possibility of parallel computation. They also proved that there is no significant loss in accuracy in their approach. They did empirically demonstrate the performance gain in speed for the case of a...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings of 9th Australasian Symposium on Parallel and Distributed Computing (AusPDC 2011)|
|Access Rights:||Open Access|
|01_Xiao_Fast_On-line_Statistical_2011.pdf||234.57 kB||Adobe PDF|
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