Pseudorandom generators for low degree polynomials

Algorithmic derandomization studies whether the output of randomized 
computations is affected when the random source is replaced with a 
pseudorandom source that uses much less randomness.  For a fixed class 
of computations, the amount of randomness that must be used by the 
pseudorandom source can be lower bounded by a counting argument.  A 
pseudorandom source is considered "optimal" if the amount of randomness 
it uses matches this lower bound.

There are only few classes of computations for which efficient 
constructions of close to optimal pseudorandom sources are known.  I 
will present a construction of such sources for the class of 
computations described by low-degree polynomials over a sufficiently 
large field.