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Each element in
the curvature
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matrix specifies
how the
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gradient in one
direction
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changes as we
move in some
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other direction.
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For a linear
network with a
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squared error,
the curvature
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matrix of the
error, E, is the
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covariance
matrix of the inputs.
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The reason
steepest descent
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goes wrong is
that the ratio of
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the magnitudes of
the
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gradients for
different weights
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changes as we
move down the
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gradient.
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