The first primality tests using randomized algorithms (based on refinements to Fermat’s little theorem) ushered in a new era. Problem after problem turned out to be far easier to solve with randomness ...

As with all "classic algorithms," its output was deterministic: it produced the same result for the same input every time. It would always finish, and it always produced the optimal, correct result.

Or you could use a more reliable, deterministic algorithm, but at a heavy computational cost. In May, a team of computer scientists showed that a kind of hybrid approach could also work. They ...

Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.

COMP_SCI 396, 496: Randomized Algorithms VIEW ALL COURSE TIMES AND SESSIONS Prerequisites 336 or Permission of the instructor, ... several algorithms have been designed which crucially use randomness ...

Bias in algorithms doesn’t necessarily mean they’re useless. But Dressel and Farid—like many others in their field—are trying to warn against putting too much faith in these numbers.