The expected number of picks needed equals the sum of the probabilities that at least $t$ picks are needed, which means that $t-1$ subsets left at least one value uncovered. We can use inclusion-exclusion to get the probability that at least one value is uncovered.
The probability that a particular set of $k$ values is uncovered after $t-1$ subsets are chosen is
$$Bigg(frac{n-k choose r}{n choose r}Bigg)^{t-1}$$
So, by inclusion-exclusion, the probability that at least one value is uncovered is
$$ sum_{k=1}^n {n choose k}(-1)^{k-1}Bigg(frac{n-k choose r}{n choose r}Bigg) ^{t-1} $$
And then the expected number of subsets needed to cover everything is
$$ sum_{t=1}^infty sum_{k=1}^n {n choose k}(-1)^{k-1} Bigg(frac{n-k choose r}{n choose r}Bigg)^{t-1} $$
Change the order of summation and use $s=t-1$:
$$ sum_{k=1}^n {n choose k}(-1)^{k-1} sum_{s=0}^infty Bigg( frac{n-k choose r}{n choose r}Bigg)^s$$
The inner sum is a geometric series.
$$ sum_{k=1}^n {n choose k} (-1)^{k-1}frac{n choose r}{{n choose r}-{n-k choose r}}$$
$$ {n choose r} sum_{k=1}^n (-1)^{k-1}frac{n choose k}{{n choose r}-{n-k choose r}}$$
I'm sure that should simplify further, but at least now it's a simple sum. I've checked that this agrees with the coupon collection problem for $r=1$.
Interestingly, Mathematica "simplifies" this sum for particular values of $r$, although what it returns even for the next case is too complicated to repeat, involving EulerGamma, the gamma function at half-integer values, and PolyGamma[0,1+n].
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