Improving the Performance of Splitting-Based Algorithms for Linear Inverse Problems
Emrah Bostan, EPFL STI LIB
Splitting-based algorithms are commonly used for linear inverse problems as they take advantage of the separable nature of these problems. Although, this kind of algorithms are very efficient for a wide range of inverse problems, they suffer from being sensitive to parameter selection. In this talk, we will briefly review splitting-based algorithms, explain their drawbacks and propose different methods to increase their robustness. Further, we will compare the performance of these algorithms with other methods for high dimensional nonconvex problems.
Emrah Bostan, EPFL STI LIB
Seminar • 23 July 2012 • BM 4.233
AbstractSplitting-based algorithms are commonly used for linear inverse problems as they take advantage of the separable nature of these problems. Although, this kind of algorithms are very efficient for a wide range of inverse problems, they suffer from being sensitive to parameter selection. In this talk, we will briefly review splitting-based algorithms, explain their drawbacks and propose different methods to increase their robustness. Further, we will compare the performance of these algorithms with other methods for high dimensional nonconvex problems.