Algorithms and Complexity of Continuous Problems

Summary

Many problems in science and engineering are described by continuous models. Yet, most work to date on computational complexity has been for combinatorial or algebraic complexity. Recently there has been considerable research on the complexity of continuous problems and the Dagstuhl-Seminar was devoted to this subject. The topics, listed below in alphabetical order, are typical of the subjects covered at the Workshop. We list both theoretical and applied topics.

Theoretical Topics

• Average Case Complexity
• Complexity of Nonlinear Problems
• Complexity of Parallel Computation
• Computational Models
• Intractable Problems
• Noisy Data
• Probabilistic Complexity
• Randomization (Monte Carlo Methods)
• Worst Case Complexity

Applications

• Approximation
• Control Theory
• Ill-Posed Problems
• Integral Equations
• Large Eigenvalue Problems
• Large Linear Systems
• Linear Optimization
• Multivariate Integration
• Nonlinear Equations
• Nonlinear Optimization
• Ordinary Differential Equations
• Partial Differential Equations
• Prediction and Estimation
• Signal Processing
• Zeros of Systems of Polynomials