Many of the computer vision algorithms have been posed in various forms of differential equations, derived from minimization of specific energy functionals, and the finite eleme...
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
We study Hamming versions of two classical clustering problems. The Hamming radius p-clustering problem (HRC) for a set S of k binary strings, each of length n, is to find p bina...
Existing profile-guided partial redundancy elimination (PRE) methods use speculation to enable the removal of partial redundancies along more frequently executed paths at the expe...
We propose a polynomial-time algorithm for segmentation
and (open) boundary estimation which takes into account
a series of user-specified attraction points. In contrast
to exis...
Thomas Windheuser, Thomas Schoenemann, Daniel Crem...