This paper studies global ranking problem by learning to rank methods. Conventional learning to rank methods are usually designed for `local ranking', in the sense that the r...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...
We extend the Bayesian skill rating system TrueSkill to infer entire time series of skills of players by smoothing through time instead of filtering. The skill of each participat...
Pierre Dangauthier, Ralf Herbrich, Tom Minka, Thor...
Confidence measures for the generalization error are crucial when small training samples are used to construct classifiers. A common approach is to estimate the generalization err...
Three-dimensional animation sequences are often represented by a discrete set of compatible triangle meshes. In order to create the illusion of a smooth motion, a sequence usually...
Tim Winkler, Jens Drieseberg, Kai Hormann, Alexand...
We investigate the connection between part of speech (POS) distribution and content in language. We define POS blocks to be groups of parts of speech. We hypothesise that there ex...