| dc.contributor.advisor | Michael Collins. | en_US |
| dc.contributor.author | Chang, Yin-Wen, S.M. Massachusetts Institute of Technology | en_US |
| dc.contributor.other | Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. | en_US |
| dc.date.accessioned | 2012-05-15T21:12:46Z | |
| dc.date.available | 2012-05-15T21:12:46Z | |
| dc.date.copyright | 2012 | en_US |
| dc.date.issued | 2012 | en_US |
| dc.identifier.uri | http://hdl.handle.net/1721.1/70791 | |
| dc.description | Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012. | en_US |
| dc.description | Cataloged from PDF version of thesis. | en_US |
| dc.description | Includes bibliographical references (p. 69-72). | en_US |
| dc.description.abstract | This thesis describes two algorithms for exact decoding of phrase-based translation models, based on Lagrangian relaxation. Both methods recovers exact solutions, with certificates of optimality, on over 99% of test examples. The first method is much more efficient than approaches based on linear programming (LP) or integer linear programming (ILP) solvers: these methods are not feasible for anything other than short sentences. We compare our methods to MOSES [6], and give precise estimates of the number and magnitude of search errors that MOSES makes. | en_US |
| dc.description.statementofresponsibility | by Yin-Wen Chang. | en_US |
| dc.format.extent | 72 p. | en_US |
| dc.language.iso | eng | en_US |
| dc.publisher | Massachusetts Institute of Technology | en_US |
| dc.rights | M.I.T. theses are protected by
copyright. They may be viewed from this source for any purpose, but
reproduction or distribution in any format is prohibited without written
permission. See provided URL for inquiries about permission. | en_US |
| dc.rights.uri | http://dspace.mit.edu/handle/1721.1/7582 | en_US |
| dc.subject | Electrical Engineering and Computer Science. | en_US |
| dc.title | Exact decoding of phrase-based translation models through Lagrangian relaxation | en_US |
| dc.type | Thesis | en_US |
| dc.description.degree | S.M. | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | |
| dc.identifier.oclc | 792849402 | en_US |
