In this paper we study the problem of classifier learning where the input data contains unjustified dependencies between some data attributes and the class label. Such cases arise...
Abstract. Researchers have focused on assessing the quality of search algorithms by measuring effort, number of mistakes, runtime distributions and other characteristics. In this p...
In this paper, we characterize the performance of an important class of scheduling schemes, called Greedy Maximal Scheduling (GMS), for multi-hop wireless networks. While a lower ...
— Generating test data for Object-Oriented (OO) software is a hard task. Little work has been done on the subject, and a lot of open problems still need to be investigated. In th...
This paper studies the optimization of observation channels (stochastic kernels) in partially observed stochastic control problems. In particular, existence, continuity, and convex...