QLEACE removes all quadratically available class information from a representation, reliably slows feedforward networks, but can inject higher-order information that lets stronger architectures learn faster.
All models have a constant depth of 2 when width is varying and a constant width of 128 when depth is varying
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Slowing Learning by Erasing Simple Features
QLEACE removes all quadratically available class information from a representation, reliably slows feedforward networks, but can inject higher-order information that lets stronger architectures learn faster.