Prof-K: Probabilistic One-Pass Filtering for Efficient Top-k Selection
Prof-K is introduced, a fast, scalable, and distribution-agnostic algorithm for exact top-k selection that derives high-probability guarantees for correctness and buffer size, together with an approximately optimal sample size that minimizes overhead as a function of N and k.
Tadeusz Dziarmaga, W. Sikora, L. Struski et al.
· 2 citations