  We consider the problem of coding for computing with maximal distortion,
where the sender communicates with a receiver, which has its own private data
and wants to compute a function of their combined data with some fidelity
constraint known to both agents. We show that the minimum rate for this problem
is equal to the conditional entropy of a hypergraph and design practical codes
for the problem. Further, the minimum rate of this problem may be a
discontinuous function of the fidelity constraint. We also consider the case
when the exact function is not known to the sender, but some approximate
function or a class to which the function belongs is known and provide
efficient achievable schemes.
