We investigate algorithmic questions that arise in the statistical problem of computing lines or hyperplanes of maximum regression depth among a set of n points. We work primarily...
Marc J. van Kreveld, Joseph S. B. Mitchell, Peter ...
In this work we revisit the Mumford-Shah functional, one
of the most studied variational approaches to image segmentation.
The contribution of this paper is to propose an
algori...
Thomas Pock, Daniel Cremers, Horst Bischof, Antoni...
The paper proposes a new wavelet-based Bayesian approach to image deconvolution, under the space-invariant blur and additive white Gaussian noise assumptions. Image deconvolution ...
Compressed Sensing is a new paradigm for acquiring the compressible signals that arise in many applications. These signals can be approximated using an amount of information much ...
Anna C. Gilbert, Martin J. Strauss, Joel A. Tropp,...
Abstract—It is important to reduce the Optical Proximity Correction (OPC) runtime while maintaining a good result quality. In this paper, we obtain a better formula, which theore...