Abstract. We propose a novel method for addressing the model selection problem in the context of kernel methods. In contrast to existing methods which rely on hold-out testing or t...
This paper describes experiments relating to the perception of the roughness of simulated surfaces via the haptic and visual senses. Subjects used a magnitude estimation technique...
Scaling conformant planning is a problem that has received much attention of late. Many planners solve the problem as a search in the space of belief states, and some heuristic gu...
The statistical perspective on boosting algorithms focuses on optimization, drawing parallels with maximum likelihood estimation for logistic regression. In this paper we present ...
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...