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arXiv · 1405.4543

A Distributed Algorithm for Training Nonlinear Kernel Machines

Dhruv Mahajan·S. Sathiya Keerthi·S. Sundararajan
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Abstract

This paper concerns the distributed training of nonlinear kernel machines on Map-Reduce. We show that a re-formulation of Nyström approximation based solution which is solved using gradient based techniques is well suited for this, especially when it is necessary to work with a large number of basis points. The main advantages of this approach are: avoidance of computing the pseudo-inverse of the kernel sub-matrix corresponding to the basis points; simplicity and efficiency of the distributed part of the computations; and, friendliness to stage-wise addition of basis points. We implement the method using an AllReduce tree on Hadoop and demonstrate its value on a few large benchmark datasets.

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Dhruv Mahajan, S. Sathiya Keerthi, S. Sundararajan. 2014-05-18. A Distributed Algorithm for Training Nonlinear Kernel Machines. https://arxiv.org/abs/1405.4543

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