While the majority of competitive image segmentation methods are based on energy minimization, only few allow to efficiently determine globally optimal solutions. A graphtheoretic...
We present a large-margin formulation and algorithm for structured output prediction that allows the use of latent variables. Our proposal covers a large range of application prob...
In this paper, we propose two new support vector approaches for ordinal regression, which optimize multiple thresholds to define parallel discriminant hyperplanes for the ordinal ...
The problem we address in this paper is that of finding effective and parsimonious patterns of connectivity in sparse associative memories. This problem must be addressed in real n...
Weiliang Chen, Reinoud Maex, Rod Adams, Volker Ste...
Abstract. In this paper we propose an original approach to solve the Inverse Kinematics problem. Our framework is based on Sequential Monte Carlo Methods and has the advantage to a...