The rapid growth of heterogeneous devices and diverse networks in our daily life, makes it is very difficult, if not impossible, to build a one-size-fits-all application or protoc...
Dynamic programming, branch-and-bound, and constraint programming are the standard solution principles for nding optimal solutions to machine scheduling problems. We propose a new ...
In this paper, we formulate the shape localization problem in the Bayesian framework. In the learning stage, we propose the Constrained RankBoost approach to model the likelihood ...
The paper introduces a new framework for feature learning in classification motivated by information theory. We first systematically study the information structure and present a n...
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...