메뉴 건너뛰기




Volumn , Issue , 2015, Pages 1516-1526

A comparison of update strategies for large-scale maximum expected BLEU training

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER AIDED LANGUAGE TRANSLATION; GRADIENT METHODS; STOCHASTIC SYSTEMS;

EID: 84960157557     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3115/v1/n15-1175     Document Type: Conference Paper
Times cited : (3)

References (43)
  • 2
    • 80053265424 scopus 로고    scopus 로고
    • A discriminative latent variable model for statistical machine translation
    • Phil Blunsom, Trevor Cohn, and Miles Osborne. 2008. A discriminative latent variable model for statistical machine translation. In Proc. of ACL-HLT.
    • (2008) Proc. of ACL-HLT
    • Blunsom, P.1    Cohn, T.2    Osborne, M.3
  • 3
    • 85044611587 scopus 로고
    • The mathematics of statistical machine translation: Parameter estimation
    • June
    • Peter F. Brown, Stephan A. Della Pietra, Vincent J. Della Pietra, and Robert L. Mercer. 1993. The Mathematics of Statistical Machine Translation: Parameter Estimation. Computational Linguistics, 19(2):263-311, June.
    • (1993) Computational Linguistics , vol.19 , Issue.2 , pp. 263-311
    • Brown, P.F.1    Della Pietra, S.A.2    Della Pietra, V.J.3    Mercer, R.L.4
  • 4
    • 22944492251 scopus 로고    scopus 로고
    • Machine translation with inferred stochastic finite-state transducers
    • Francisco Casacuberta and Enrique Vidal. 2004. Machine translation with inferred stochastic finite-state transducers. Computational Linguistics, 30(2):205-225.
    • (2004) Computational Linguistics , vol.30 , Issue.2 , pp. 205-225
    • Casacuberta, F.1    Vidal, E.2
  • 5
    • 0003396042 scopus 로고    scopus 로고
    • An empirical study of smoothing techniques for language modeling
    • Harvard University, Cambridge, MA, August
    • Stanley F. Chen and Joshuo Goodman. 1998. An Empirical Study of Smoothing Techniques for Language Modeling. Technical Report TR-10-98, Computer Science Group, Harvard University, Cambridge, MA, August.
    • (1998) Technical Report TR-10-98, Computer Science Group
    • Chen, S.F.1    Goodman, J.2
  • 9
    • 75249102673 scopus 로고    scopus 로고
    • Efficient online and batch learning using forward backward splitting
    • December
    • John Duchi and Yoram Singer. 2009. Efficient online and batch learning using forward backward splitting. Journal of Machine Learning Research, 10:2899-2934, December.
    • (2009) Journal of Machine Learning Research , vol.10 , pp. 2899-2934
    • Duchi, J.1    Singer, Y.2
  • 10
    • 80052250414 scopus 로고    scopus 로고
    • Adaptive subgradient methods for online learning and stochastic optimization
    • July
    • John Duchi, Elad Hazan, and Yoram Singer. 2011. Adaptive subgradient methods for online learning and stochastic optimization. Journal of Machine Learning Research, 12:2121-2159, July.
    • (2011) Journal of Machine Learning Research , vol.12 , pp. 2121-2159
    • Duchi, J.1    Hazan, E.2    Singer, Y.3
  • 14
    • 85122629429 scopus 로고    scopus 로고
    • An empirical comparison of features and tunign for phrase-based machine translation
    • Baltimore, Maryland, USA, June
    • Spence Green, Daniel Cer, and Christopher D. Manning. 2014. An empirical comparison of features and tunign for phrase-based machine translation. In Proceedings of the Ninth Workshop on Statistical Machine Translation, pages 466-476, Baltimore, Maryland, USA, June.
    • (2014) Proceedings of the Ninth Workshop on Statistical Machine Translation , pp. 466-476
    • Green, S.1    Cer, D.2    Manning, C.D.3
  • 16
    • 80053342679 scopus 로고    scopus 로고
    • Triplet lexicon models for statistical machine translation
    • Honolulu, Hawaii, October. Association for Computational Linguistics
    • Saša Hasan, Juri Ganitkevitch, Hermann Ney, and Jesús Andrés-Ferrer. 2008. Triplet lexicon models for statistical machine translation. In Conference on Empirical Methods in Natural Language Processing, pages 372-381, Honolulu, Hawaii, October. Association for Computational Linguistics.
    • (2008) Conference on Empirical Methods in Natural Language Processing , pp. 372-381
    • Hasan, S.1    Ganitkevitch, J.2    Ney, H.3    Andrés-Ferrer, J.4
  • 19
    • 80051618443 scopus 로고    scopus 로고
    • EM-style optimization of hidden conditional random fields for grapheme-to-phoneme conversion
    • Prague, Czech Republic, May
    • Georg Heigold, Stefan Hahn, Patrick Lehnen, and Hermann Ney. 2011. EM-Style Optimization of Hidden Conditional Random Fields for Grapheme-to-Phoneme Conversion. In IEEE International Conference on Acoustics, Speech, and Signal Processing, pages 4920-4923, Prague, Czech Republic, May.
    • (2011) IEEE International Conference on Acoustics, Speech, and Signal Processing , pp. 4920-4923
    • Heigold, G.1    Hahn, S.2    Lehnen, P.3    Ney, H.4
  • 21
    • 85011919605 scopus 로고    scopus 로고
    • A phrase orientation model for hierarchical machine translation
    • Sofia, Bulgaria, August
    • Matthias Huck, Joern Wuebker, Felix Rietig, and Hermann Ney. 2013. A phrase orientation model for hierarchical machine translation. In Workshop on Statistical Machine Translation, pages 452-463, Sofia, Bulgaria, August.
    • (2013) Workshop on Statistical Machine Translation , pp. 452-463
    • Huck, M.1    Wuebker, J.2    Rietig, F.3    Ney, H.4
  • 28
    • 84859981825 scopus 로고    scopus 로고
    • Intelligent selection of language model training data
    • Uppsala, Sweden, July
    • R.C. Moore and W. Lewis. 2010. Intelligent Selection of Language Model Training Data. In ACL (Short Papers), pages 220-224, Uppsala, Sweden, July.
    • (2010) ACL (Short Papers) , pp. 220-224
    • Moore, R.C.1    Lewis, W.2
  • 29
    • 22944469345 scopus 로고    scopus 로고
    • The alignment template approach to statistical machine translation
    • December
    • Franz Josef Och and Hermann Ney. 2004. The alignment template approach to statistical machine translation. Computational Linguistics, 30(4):417-449, December.
    • (2004) Computational Linguistics , vol.30 , Issue.4 , pp. 417-449
    • Josef Och, F.1    Ney, H.2
  • 32
    • 84943274699 scopus 로고
    • A direct adaptive method for faster backpropagation learning: The rprop algorithm
    • Martin Riedmiller and Heinrich Braun. 1993. A direct adaptive method for faster backpropagation learning: The rprop algorithm. In IEEE International Conference on Neural Networks, pages 586-591.
    • (1993) IEEE International Conference on Neural Networks , pp. 586-591
    • Riedmiller, M.1    Braun, H.2
  • 33
    • 84926161290 scopus 로고    scopus 로고
    • Discriminative training of 150 million translation parameters and its application to pruning
    • Atlanta, Georgia, June
    • Hendra Setiawan and Bowen Zhou. 2013. Discriminative training of 150 million translation parameters and its application to pruning. In NAACL-HLT 2013, pages 335-341, Atlanta, Georgia, June.
    • (2013) NAACL-HLT 2013 , pp. 335-341
    • Setiawan, H.1    Zhou, B.2
  • 34


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.