We present a neural-network-based statistical parser, trained and tested on the Penn Treebank. The neural network is used to estimate the parameters of a generative model of left-...
Echo State Networks (ESNs) have been shown to be effective for a number of tasks, including motor control, dynamic time series prediction, and memorizing musical sequences. Howeve...
Matthew H. Tong, Adam D. Bickett, Eric M. Christia...
We present a new grammar formalism for parsing with freer word-order languages, motivated by recent linguistic research in German and the Slavic languages. Unlike CFGs, these gram...
In this paper, we investigate how modeling content structure can benefit text analysis applications such as extractive summarization and sentiment analysis. This follows the lingu...
We present a machine translation framework that can incorporate arbitrary features of both input and output sentences. The core of the approach is a novel decoder based on lattice...