Constraint Driven Learning

This paper introduces a novel unsupervised constraint-driven learning algorithm for iden- tifying named-entity (NE) transliterations in bilingual corpora. The proposed method does not require any annotated data or aligned cor- …...

We present a simple method for transferring dependency parsers from source languages with labeled training data to target languages without labeled training data. We first demon- strate that delexicalized parsers …...

We present a general framework containing a graded spectrum of Expectation Maximization (EM) algorithms called Unified Expectation Maximization (UEM.) UEM is parameterized by a single parameter and covers existing al- …...