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Fast Food: Approximating Kernel Expansion in Loglinear Time
Published on Jan 18, 20139451 Views
The ability to evaluate nonlinear function classes rapidly is crucial for nonparametric estimation. We propose an improvement to random kitchen sinks that offers O(n log d) computation and O(n) st
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Chapter list
Fastfood: O(n log d) feature maps for kernels00:00
The trouble with kernels - 100:01
The trouble with kernels - 203:39
Random Kitchen Sinks04:40
Key Idea06:45
Properties09:27
Matrix approximation error11:00
Generalization Performance11:33
Speed & accuracy11:48
Summary13:01