Stochastic programming is the subfield of mathematical programming that considers optimization in the presence of uncertainty. During the last four decades a vast amount of litera...
We study the complexity of the motion planning problem for a bounded-reach robot in the situation where the n obstacles in its workspace satisfy two of the realistic models propos...
Mark de Berg, Matthew J. Katz, Mark H. Overmars, A...
We establish a new connection between the two most common traditions in the theory of real computation, the Blum-Shub-Smale model and the Computable Analysis approach. We then use...
A novel framework for the factorisation of complex-valued data is derived using recent developments in complex statistics. Unlike existing factorisation tools the algorithms can c...
While we have previously reported on multiscale segmentation of single-figure anatomic objects from medical images by deformable m-rep models, here we report on a method of segmen...
P. Thomas Fletcher, Stephen M. Pizer, A. Graham Ga...