A2. Solving practical inverse problems

Successful scientific and technological decision making depends heavily on the reliable and stable recovery of information from indirect measurements. The potential unstable impact of the uncertainty in the measurements is managed through the choice of an appropriate regularization procedure. For example, because, in many real-world situations, the relationship between the available measurements and the extent of the information to be recovered is underdetermined, additional practical and theoretical constraints must be invoked to guarantee a useful recovery of the information hidden in the measurements. In the planned session, examples from spectroscopy, risk hedging and rheology will be discussed along with some novel solution strategies. In particular, derivative spectroscopy and resolution enhancement information recovery from spectra, the solution of the interconversion of linear viscoelasticity, $L_1$ fitting in risk hedging and robust cross-validation estimation will be discussed.