The DOE SC program in Advanced Scientific Computing Research (ASCR) hereby announces its interest in basic research in the design, development, analysis, and scalability of randomized algorithms for ...

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 ...

In terms of inconsistent conclusions across all relevant randomized controlled trials (RCTs) and available meta-analyses, we aimed to use a meta-analysis and trial sequential analysis (TSA) to ...

Algorithm design and analysis is fundamental to all areas of computer science and gives a rigorous framework for the study optimization. This course provides an introduction to algorithm design ...

Background: The provision of nutritional support for patients in intensive care units (ICUs) varies widely both within and between institutions. We tested the hypothesis that evidence-based algorithms ...

In this module, we will learn randomized pivot selection for quicksort and quickselect. We will learn how to analyze the complexity of the randomized quicksort/quickselect algorithms. We will learn ...

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, [email protected] ... In the last 30+ years, several algorithms ...

Algorithm design strategies such as divide and conquer. Elementary techniques for analysis; asymptotic analysis, recursion equations, estimation methods, elementary combinatorial arguments.

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 ...