Stochastic context-free grammars (SCFGs) have long been recognized as useful for a large variety of tasks including natural language processing, morphological parsing, speech reco...
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 propose a novel technique for semi-supervised image annotation which introduces a harmonic regularizer based on the graph Laplacian of the data into the probabilistic semantic ...
Yuanlong Shao, Yuan Zhou, Xiaofei He, Deng Cai, Hu...
The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building large-scale multivariate stat...
ct tasks such as extraction of relational information from text [Young] [Jacobs]. We describe a method for classifying news stories using Alternative systems [Biebricher] [Lewis] u...