In this paper, we investigate a simple, mistakedriven learning algorithm for discriminative training of continuous density hidden Markov models (CD-HMMs). Most CD-HMMs for automat...
Building of atlases representing average and variability of a population of images or of segmented objects is a key topic in application areas like brain mapping, deformable objec...
Shun Xu, Martin Andreas Styner, Brad Davis, Sarang...
We describe a framework of bootstrapped hypothesis testing for estimating the confidence in one web search engine outperforming another over any randomly sampled query set of a gi...
Eric C. Jensen, Steven M. Beitzel, Ophir Frieder, ...
To satisfy potential customers of a Web site and to lead them to the goods offered by the site, one should support them in the course of navigation they have embarked on. This pape...
This paper presents collaborative decoding (co-decoding), a new method to improve machine translation accuracy by leveraging translation consensus between multiple machine transla...
Mu Li, Nan Duan, Dongdong Zhang, Chi-Ho Li, Ming Z...