Numerical methods for optimal experimental design of ill-posed problem

Event Details
  • Date/Time:
    • Monday September 15, 2008
      3:00 pm - 4:00 pm
  • Location: Executive classroom 228
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    $0.00
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Contact
Anita Race
H. Milton Stewart School of Industrial and Systems Engineering
Contact Anita Race
Summaries

Summary Sentence: Numerical methods for optimal experimental design of ill-posed problem

Full Summary: Numerical methods for optimal experimental design of ill-posed problems

TITLE: Numerical methods for optimal experimental design of ill-posed problems

SPEAKER: Dr. Eldad Haber

ABSTRACT:

While experimental design for well-posed inverse linear problems has been well studied, covering a vast range of well-established design criteria and optimization algorithms, its ill-posed counterpart is a rather new topic. The ill-posed nature of the problem entails the incorporation of regularization techniques. The consequent non-stochastic error introduced by regularization, needs to be taken into account when choosing an experimental design. We discuss different ways to define an optimal design that controls both an average total error of regularized estimates and a measure of the total cost of the design. We also introduce a numerical framework that efficiently implements such designs and natively allows for the solution of large-scale problems. To illustrate the possible applications of the methodology, we consider a borehole tomography example and a two-dimensional function recovery problem.

Contact: ISyE DOS Optimization Seminars (http://www2.isye.gatech.edu/dos/)

Additional Information

In Campus Calendar
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H. Milton Stewart School of Industrial and Systems Engineering (ISYE)

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Categories
Seminar/Lecture/Colloquium
Keywords
Linear, optimization
Status
  • Created By: Anita Race
  • Workflow Status: Published
  • Created On: Oct 12, 2009 - 4:38pm
  • Last Updated: Oct 7, 2016 - 9:47pm