Delaying projections in EigenPro-style kernel training cuts the amortized per-batch cost from quadratic to linear in model size, yielding up to hundreds of times faster training at comparable accuracy.
On the nystrom approximation for preconditioning in kernel machines
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Fast training of large kernel models with delayed projections
Delaying projections in EigenPro-style kernel training cuts the amortized per-batch cost from quadratic to linear in model size, yielding up to hundreds of times faster training at comparable accuracy.