We propose a Bayesian framework for representing and recognizing local image motion in terms of two basic models: translational motion and motion boundaries. Motion boundaries are ...
Most previous research into the job-shop scheduling problem has concentrated on finding a single optimal solution (e.g., makespan), even though the actual requirement of most prod...
— This paper presents a multi-skill motion planner which is able to sequentially synchronize parameterized motion skills in order to achieve humanoid motions exhibiting complex w...
The present article considers estimating a parameter θ in an imprecise probability model (Pθ)θ∈Θ which consists of coherent upper previsions Pθ . After the definition of a...
We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...