We study sensor minimization problems in the context of fault diagnosis. Fault diagnosis consists in synthesizing a diagnoser that observes a given plant and identifies faults in...
In this work we present a unified view on Markov random fields and recently proposed continuous tight convex relaxations for multi-label assignment in the image plane. These rel...
The problem of target localization involves estimating the position of a target from multiple and typically noisy measurements of the target position. It is well known that the re...
Adrian N. Bishop, Baris Fidan, Brian D. O. Anderso...
We extend the well-known BFGS quasi-Newton method and its memory-limited variant LBFGS to the optimization of nonsmooth convex objectives. This is done in a rigorous fashion by ge...
Regression test suites tend to grow over time as new test cases are added to exercise new functionality or to target newly-discovered faults. When test suites become too large, th...