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 ...
The “Demons Algorithm” in increasingly used for non-rigid registration of 3D medical images. However, if it is fast and usually accurate, the algorithm is based on intuitive id...
We describe our experience with a new algorithm for the reconstruction of surfaces from unorganized sample points in IR 3. The algorithm is the first for this problem with provab...
Nina Amenta, Marshall W. Bern, Manolis Kamvysselis
: Recurrent neural networks possess interesting universal approximation capabilities, making them good candidates for time series modeling. Unfortunately, long term dependencies ar...
In recent years there has been a flurry of works on learning Bayesian networks from data. One of the hard problems in this area is how to effectively learn the structure of a beli...