This paper closes a gap in the foundations of the theory of average case complexity. First, we clarify the notion of a feasible solution for a search problem and prove its robustne...
This paper proposes the use of uncertainty reduction in machine learning methods such as co-training and bilingual bootstrapping, which are referred to, in a general term, as ‘c...
Generalized additive models (GAM) for modelling nonlinear effects of continuous covariates are now well established tools for the applied statistician. In this paper we develop Ba...
Abstract. Over the past few years researchers have been investigating the enhancement of visual tracking performance by devising trackers that simultaneously make use of several di...
The Errors-in-Variables (EIV) model from statistics is often employed in computer vision thoughonlyrarely under this name. In an EIV model all the measurements are corrupted by no...