We present a data-driven variant of the LR algorithm for dependency parsing, and extend it with a best-first search for probabilistic generalized LR dependency parsing. Parser act...
This paper presents the development of two related machine-learned models which predict (a) whether a student can answer correctly questions in an ILE without requesting help and (...
AND/OR search spaces have recently been introduced as a unifying paradigm for advanced algorithmic schemes for graphical models. The main virtue of this representation is its sens...
This paper describes work done as part of the Oxford AGV (Autonomous Guided Vehicle) project [2] towards recognition of classes of objects to be encountered in a factory environme...
In this paper, a novel standard variance feature is proposed for background modeling in dynamic scenes involving waving trees and ripples in water. The standard variance feature i...