Learn about the benefits and challenges of using randomized algorithms in AI applications, such as efficiency, robustness, complexity, and quality.

I won't be asking you about the randomized algorithm for Min-Cut which we haven't covered in class. I may ask some basic questions on randomized algorithms (and basic probability theory that we saw in ...

Randomized algorithms for very large matrix problems have received a great deal of attention in recent years. Much of this work was motivated by problems in large-scale data analysis, largely since ...

This study develops and implements a machine learning model to forecast expenditures in HICC Grants and Contributions programs, focusing on reimbursement-based claims. A comparative analysis of ...

In a new study, researchers have developed a new algorithm that increases the amount of certified randomness in a sequence of seemingly random numbers that has been generated experimentally.

Matching algorithms to application characteristics Within any application category or set of characteristics there are many optimization algorithms that are equivalently effective. Criteria for ...

We describe two recently proposed randomized algorithms for the construction of low-rank approximations to matrices, and demonstrate their application (inter alia) to the evaluation of the singular ...

DOE Randomized Algorithms for Combinatorial Scientific ComputingPlease see the full solicitation for complete information about the funding opportunity. Below is a summary assembled by the Research & ...