A Tutorial on Dual Decomposition and Lagrangian Relaxation for Inference in Natural Language Processing
Dual decomposition, and more generally Lagrangian relaxation, is a classical method for combinatorial optimization; it has recently been applied to several inference problems in natural language processing (NLP). This tutorial gives an overview of the technique. We describe example algorithms, descr...
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| Format: | Article |
| Language: | en_US |
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Association for the Advancement of Artificial Intelligence
2013
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| Online Access: | http://hdl.handle.net/1721.1/77624 |