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Bengio and Frasconi 
propose a probabilistic approach for propagating targets.
With so-called ``state networks'', at a given
time, their system
can be in one of only different discrete states.
adjusted using the expectation-maximization algorithm.
But to solve problems that require a significant amount of memory to
store contextual information,
such systems would require an unacceptable number
of states (i.e., state networks).