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Global Optimization and Uncertainty Quantification


Prof. Mrinal K. Sen

The University of Texas at Austin

12 hours (3 hours/day) – 3 CFU
June 19 - June 22, 2017
Prerequisites: Basic knowledge of statistics, matrix algebra and MATLAB
Short Program of the Course:
·         Introduction to inverse problems - why they are hard?
·         Objective functions and Norm
·         Local Optimization methods
·         Statistical methods for inversion
·         Monte Carlo Markov Chain (MCMC)
·         Simulated Annealing
·         Genetic Algorithms
·         Particle Swarm Optimization
·         Uncertainty quantification: Fixed Dimensional problem
·         Uncertainty quantification: Trans-dimensional problem
·         Computer exercises about MCMC and SA
To register and query, please contact: chauhan@unina.it