  The Median of Medians (also known as BFPRT) algorithm, although a landmark
theoretical achievement, is seldom used in practice because it and its variants
are slower than simple approaches based on sampling. The main contribution of
this paper is a fast linear-time deterministic selection algorithm
QuickselectAdaptive based on a refined definition of MedianOfMedians. The
algorithm's performance brings deterministic selection---along with its
desirable properties of reproducible runs, predictable run times, and immunity
to pathological inputs---in the range of practicality. We demonstrate results
on independent and identically distributed random inputs and on
normally-distributed inputs. Measurements show that QuickselectAdaptive is
faster than state-of-the-art baselines.
