We explore how to improve machine translation systems by adding more translation data in situations where we already have substantial resources. The main challenge is how to buck ...
In this work, we model the writing revision process of English as a Second Language (ESL) students with syntaxdriven machine translation methods. We compare two approaches: tree-t...
We propose a generative model based on Temporal Restricted Boltzmann Machines for transition based dependency parsing. The parse tree is built incrementally using a shiftreduce pa...
We propose several techniques for improving statistical machine translation between closely-related languages with scarce resources. We use character-level translation trained on ...
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...