The bootstrap has become a popular method for exploring model (structure) uncertainty. Our experiments with artificial and realworld data demonstrate that the graphs learned from...
This paper describes recent advances in hidden Markov model (HMM) based OCR for machine-printed Arabic documents. A combination of scriptindependent and script-specific techniques...
Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
We propose a language model based on a precise, linguistically motivated grammar (a hand-crafted Head-driven Phrase Structure Grammar) and a statistical model estimating the proba...
This paper presents a new approach to largevocabulary online handwritten Chinese character recognition based on semi-tied covariance (STC) modeling. Detailed procedures are descri...