We introduce a semi-supervised approach to training for statistical machine translation that alternates the traditional Expectation Maximization step that is applied on a large tr...
This paper analyses the Contrastive Divergence algorithm for learning statistical parameters. We relate the algorithm to the stochastic approximation literature. This enables us t...
Statistical relational learning (SRL) algorithms learn statistical models from relational data, such as that stored in a relational database. We previously introduced view learnin...
Jesse Davis, Irene M. Ong, Jan Struyf, Elizabeth S...
We propose a structure called dependency forest for statistical machine translation. A dependency forest compactly represents multiple dependency trees. We develop new algorithms ...
Zhaopeng Tu, Yang Liu, Young-Sook Hwang, Qun Liu, ...
Statistical machine learning continues to show promise as a tool for addressing complex problems in a variety of domains. An increasing number of developers are therefore looking ...
Kayur Patel, James Fogarty, James A. Landay, Bever...