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 ...

The bookshelf problem (which computer scientists call the “list labeling” problem) is one of the most basic topics in the field of data structures. “It’s the kind of problem you’d teach to freshman or ...

It may come as a surprise that despite the power our computers have, they can't achieve true randomness. In fact, they rely ...

Much of the business world, and nearly all healthcare decisions, are still made based on deterministic "rules." If your heart rate is above 100 bpm, you'll be classified as high risk.

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 ...

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 ...

Randomized algorithms have become an essential tool in solving linear systems and least squares problems, particularly in large-scale applications. These algorithms leverage randomness to improve ...

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 ...

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.