Tuesday, 13:45 - 14:10 h, Room: H 2036

 

Martin Lotz
Conditioning of the convex feasibility problem and sparse recovery

Coauthor: Dennis Amelunxen

 

Abstract:
The problem of whether certain simple or sparse solutions to linear systems of equations can be found or approximated efficiently can often be cast in terms of a convex feasibility problem. In particular, condition numbers introduced for the complexity analysis of conic optimization problems play an important role in the analysis of such problems. We present results and geometric methods from the probabilistic analysis of condition numbers for optimization problems, and indicate how this analysis can be used to obtain sparse and simple recovery thresholds for problems with noise.

 

Talk 2 of the invited session Tue.2.H 2036
"Advances in convex optimization" [...]
Cluster 4
"Conic programming" [...]

 

  There are three major facts that should be watched out for in all payday loans in the United States. Since its introduction in the market buying Order Cialis can be exclusively in pharmacy chains with a prescription from a doctor. I agree that this is very inconvenient and takes a lot of time and effort.