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.

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 ...

Over the years, as computational power grew exponentially, well-studied and deterministic algorithms increasingly gave way to AI systems impervious to rigorous human inspection. Much like how the ...

In a 1977 proof, for example, Robert Solovay and Volker Strassen introduced a randomized algorithm that could determine whether a number is prime faster than the best deterministic algorithms of that ...

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.

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.

This course will discuss fundamental concepts and tools in discrete mathematics with emphasis on their applications to computer science. Example topics include logic and Boolean circuits; sets, ...