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Optimal Design in Large-Scale Inversion - From Compressive to Comprehensive Sensing

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If you have a question about this talk, please contact Mustapha Amrani.

Inverse Problems

Co-authors: Eldad Haber (UBC), Luis Tenorio (CSM)

In the quest for improving inversion fidelity of large-scale problems, great consideration has been devoted towards effective solution of ill-posed problems of various regularization configurations. Nevertheless, complementary issues, such as determination of optimal configurations for data acquisition or more generally any other controllable parameters of the apparatus and process were frequently overlooked. While optimal design for well-posed problems has been extensively studied in the past, little consideration has been directed to its ill-posed counterpart. This is strikingly in contrast to the fact that a broad range of real-life problems are of such nature. In this talk, some of the intrinsic difficulties associated with design for ill-posed inverse problems shall be described, further, a coherent formulation to address these challenges will be laid out and finally the importance of design for various inversion problems shall be demonstrated.

Related Links: – Design in Inversion – Open Collaboration Research,d.eW0 – Optimal Design for Large-Scale Ill-Posed Problems – Slide deck

This talk is part of the Isaac Newton Institute Seminar Series series.

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