Algorithms are used to perform a host of critical tasks, such as classification, pattern recognition, regression, dimension reduction, streaming, and sketching to give provable guarantees in a bounded amount of time and space. Fundamental algorithmic research looks at ways to develop new approaches to problems to potentially offer dramatic performance improvements. Researchers also look at tradeoffs between efficiency and performance guarantees in order to refine the problem specifications, when appropriate, to offer far more scalable solutions.
Algorithms and Randomness Center (ARC)
Eric Vigoda, Director
Center members explore the design of efficient algorithms and the limits of computation. Extracting information from data is an enormous challenge requiring insights from algorithms, optimization, and statistics, among others.
