Polynomial time preprocessing to reduce instance size is one of the most commonly deployed heuristics to tackle computationally hard problems. In a parameterized problem, every in...
Hans L. Bodlaender, Fedor V. Fomin, Daniel Lokshta...
We address covariance estimation under mean-squared loss in the Gaussian setting. Specifically, we consider shrinkage methods which are suitable for high dimensional problems wit...
The visualization of 3D vector and tensor fields in a 2D image is challenging because the large amount of information will either be mixed during projection to 2D or lead to seve...
In this paper we show how common speech recognition training criteria such as the Minimum Phone Error criterion or the Maximum Mutual Information criterion can be extended to inco...
Given a set of rectangles with fixed orientations, we want to find an enclosing rectangle of minimum area that contains them all with no overlap. Many simple scheduling tasks ca...