Stochastic Optimization with Learning for Complex Problems
DESCRIPTION: To evaluate the effectiveness of learning techniques for improving the performance of stochastic optimization on domain-specific CAD problems.
To statistically characterize a number of important CAD problems.
To evaluate the potential of learning techniques (e.g. Bayesian, SVMs) for improving the expected performance of stochastic optimization on these problems over time.
To implement a learning-stochastic-optimizer based on the above results and apply it to representative CAD problems.