We consider sensor scheduling as the optimal observability problem for partially observable Markov decision processes (POMDP). This model fits to the cases where a Markov process ...
The Dantzig selector is a near ideal estimator for recovery of sparse signals from linear measurements in the presence of noise. It is a convex optimization problem which can be r...
Abstract— We recast the problem of unconstrained continuous evolutionary optimization as inference in a fixed graphical model. This approach allows us to address several pervasi...
Christopher K. Monson, Kevin D. Seppi, James L. Ca...
In recent years dynamic optimization problems have attracted a growing interest from the community of genetic algorithms with several approaches developed to address these problems...
Finding contours in constrained search space is a well known problem. It is encountered in such areas as tracking objects in videos, or finding objects within defined boundaries....