  The bias/variance tradeoff is fundamental to learning: increasing a model's
complexity can improve its fit on training data, but potentially worsens
performance on future samples. Remarkably, however, the human brain
effortlessly handles a wide-range of complex pattern recognition tasks. On the
basis of these conflicting observations, it has been argued that useful biases
in the form of "generic mechanisms for representation" must be hardwired into
cortex (Geman et al).
  This note describes a useful bias that encourages cooperative learning which
is both biologically plausible and rigorously justified.
