Compressed Counting (CC), based on maximally skewed stable random
projections, was recently proposed for estimating the p-th frequency moments of
data streams. The case p->1 is extremely useful for estimating Shannon entropy
of data streams. In this study, we provide a very simple algorithm based on the
sample minimum estimator and prove a much improved sample complexity bound,
compared to prior results.