acl acl2013 acl2013-251 acl2013-251-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Vladimir Eidelman ; Ke Wu ; Ferhan Ture ; Philip Resnik ; Jimmy Lin
Abstract: We present an open-source framework for large-scale online structured learning. Developed with the flexibility to handle cost-augmented inference problems such as statistical machine translation (SMT), our large-margin learner can be used with any decoder. Integration with MapReduce using Hadoop streaming allows efficient scaling with increasing size of training data. Although designed with a focus on SMT, the decoder-agnostic design of our learner allows easy future extension to other structured learning problems such as sequence labeling and parsing.