Algorithms and Complexity for Continuous Problems

Scope

Theoretical and applied research on algorithms and complexity for continuous problems

Scientific Motivation

Continuous computational problems arise in diverse areas of science and engineering. There is great interest in computational aspects of multivariate problems. Examples include path and multivariate integration, function approximation, optimization, differential, integral and operator equations. Understanding the complexity of such problems and construction of efficient algorithms is both important and challenging.

An exciting area of research is algorithms and complexity for quantum computation. There will be a number of talks in this area. The study of quantum algorithms and complexity for continuous problems was recently initiated and will be discussed.

A major focus of the Workshop will continue to be the complexity of high dimensional problems and their tractability. Efficient or, ideally, optimal algorithms will be presented. Since Monte Carlo and/or quasi-Monte Carlo algorithms are often used for such problems, their efficiency will be addressed. There will be a number of talks on applications to finance. Models of computation and various settings (e.g., worst case, average case, or probabilistic) are important parts of the complexity study and these will be discussed as well.

Selected papers from the workshop will be published in a special issue of the Journal of Complexity.