Relying on optimally distinguishable distributions (ODD), it was defined very recently a new framework for the composite hypothesis testing. We resort to the linear model to inve...
We present and evaluate a framework and tool for combining multiple program analyses which allows the dynamic (on-line) adjustment of the precision of each analysis depending on t...
The paper proposes a reliable method for estimating quadric surfaces from 3D range data in the framework of object recognition and localization or object modelling. Instead of est...
Naoufel Werghi, Anthony Ashbrook, Robert B. Fisher...
Many machine learning algorithms can be formulated in the framework of statistical independence such as the Hilbert Schmidt Independence Criterion. In this paper, we extend this c...
Xinhua Zhang, Le Song, Arthur Gretton, Alex J. Smo...
We present a new method of selecting the best of several competing system designs on the basis of expected steadystate performance. The method uses a new form of timeseries bootst...