The Discrete Pascal Transform (DPT) has been proved remarkably useful for edge detection, filter design, discrete-time signal interpolation and data hiding. In the present work a n...
Abstract. Often the information present in a spatial knowledge base is represented at a different level of granularity and abstraction than the query constraints. For querying onto...
Prateek Jain, Peter Z. Yeh, Kunal Verma, Cory A. H...
Linear decompressors are the dominant methodology used in commercial test data compression tools. However, they are generally not able to exploit correlations in the test data, an...
Covariance estimation for high dimensional vectors is a classically difficult problem in statistical analysis and machine learning. In this paper, we propose a maximum likelihood ...
In this paper we present a novel approach for expanding spherical 3D-tensor fields of arbitrary order in terms of a tensor valued local Fourier basis. For an efficient implementati...
Henrik Skibbe, Marco Reisert, Thorsten Schmidt, Kl...