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First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. The paper proposes to use random functions as an approximation to kernel functions and then proposes to do stochastic gradient descent. Convergence rates and generalisation bounds are derived. Experimental results on large datasets are presented. The idea of introducing random functions to approximate kernel functions and then using SGD is very interesting.