메뉴 건너뛰기




Volumn , Issue , 2010, Pages 751-759

From baby steps to leapfrog: How "Less is more" in unsupervised dependency parsing

Author keywords

[No Author keywords available]

Indexed keywords

DATA COMPLEXITY; DEPENDENCY MODEL; DEPENDENCY PARSING; GRAMMAR INDUCTION; ITERATED LEARNING; LOW-COMPLEXITY; TRAINING SETS; UNSUPERVISED ALGORITHMS; WALL STREET JOURNAL;

EID: 84858423134     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (185)

References (45)
  • 3
    • 0030353367 scopus 로고    scopus 로고
    • Head automata for speech translation
    • H. Alshawi. 1996. Head automata for speech translation. In Proc. of ICSLP.
    • (1996) Proc. of ICSLP
    • Alshawi, H.1
  • 7
    • 84859885240 scopus 로고    scopus 로고
    • Coarse-to-fine n-best parsing and MaxEnt discriminative reranking
    • E. Charniak and M. Johnson. 2005. Coarse-to-fine n-best parsing and MaxEnt discriminative reranking. In Proc. of ACL.
    • (2005) Proc. of ACL
    • Charniak, E.1    Johnson, M.2
  • 9
    • 84858398441 scopus 로고    scopus 로고
    • Shared logistic normal distributions for soft parameter tying in unsupervised grammar induction
    • S. B. Cohen and N. A. Smith. 2009. Shared logistic normal distributions for soft parameter tying in unsupervised grammar induction. In Proc. of NAACL-HLT.
    • (2009) Proc. of NAACL-HLT
    • Cohen, S.B.1    Smith, N.A.2
  • 10
    • 85098437012 scopus 로고    scopus 로고
    • Logistic normal priors for unsupervised probabilistic grammar induction
    • S. B. Cohen, K. Gimpel, and N. A. Smith. 2008. Logistic normal priors for unsupervised probabilistic grammar induction. In NIPS.
    • (2008) NIPS
    • Cohen, S.B.1    Gimpel, K.2    Smith, N.A.3
  • 13
    • 0027636611 scopus 로고
    • Learning and development in neural networks: The importance of starting small
    • J. L. Elman. 1993. Learning and development in neural networks: The importance of starting small. Cognition, 48.
    • (1993) Cognition , pp. 48
    • Elman, J.L.1
  • 14
    • 84858394602 scopus 로고
    • Does baum-welch re-estimation help taggers?
    • D. Elworthy. 1994. Does Baum-Welch re-estimation help taggers? In Proc. of ANLP.
    • (1994) Proc. of ANLP
    • Elworthy, D.1
  • 16
    • 0031211090 scopus 로고    scopus 로고
    • A decision-theoretic generalization of on-line learning and an application to boosting
    • Y. Freund and R. E. Schapire. 1997. A decision-theoretic generalization of on-line learning and an application to boosting. Journal of Computer and System Sciences, 55(1).
    • (1997) Journal of Computer and System Sciences , vol.55 , Issue.1
    • Freund, Y.1    Schapire, R.E.2
  • 18
    • 84863408489 scopus 로고    scopus 로고
    • Improving unsupervised dependency parsing with richer contexts and smoothing
    • W. P. Headden, III, M. Johnson, and D. McClosky. 2009. Improving unsupervised dependency parsing with richer contexts and smoothing. In Proc. of NAACL-HLT.
    • (2009) Proc. of NAACL-HLT
    • Headden, W.P.1    Johnson III, M.2    McClosky, D.3
  • 20
    • 29344466697 scopus 로고    scopus 로고
    • Corpus-based induction of syntactic structure: Models of dependency and constituency
    • D. Klein and C. D. Manning. 2004. Corpus-based induction of syntactic structure: Models of dependency and constituency. In Proc. of ACL.
    • (2004) Proc. of ACL
    • Klein, D.1    Manning, C.D.2
  • 22
    • 59649113160 scopus 로고    scopus 로고
    • Flexible shaping: How learning in small steps helps
    • K. A. Krueger and P. Dayan. 2009. Flexible shaping: How learning in small steps helps. Cognition, 110.
    • (2009) Cognition , pp. 110
    • Krueger, K.A.1    Dayan, P.2
  • 23
    • 84862295871 scopus 로고    scopus 로고
    • Analyzing the errors of unsupervised learning
    • P. Liang and D. Klein. 2008. Analyzing the errors of unsupervised learning. In Proc. of HLT-ACL.
    • (2008) Proc. of HLT-ACL
    • Liang, P.1    Klein, D.2
  • 27
    • 84867119745 scopus 로고
    • Tagging English text with a probabilistic model
    • B. Merialdo. 1994. Tagging English text with a probabilistic model. Computational Linguistics, 20(2):155-172.
    • (1994) Computational Linguistics , vol.20 , Issue.2 , pp. 155-172
    • Merialdo, B.1
  • 28
    • 0000044388 scopus 로고
    • Constraints on learning and their role in language acquisition: Studies of the acquisition of American sign language
    • E. L. Newport. 1988. Constraints on learning and their role in language acquisition: Studies of the acquisition of American Sign Language. Language Sciences, 10(1).
    • (1988) Language Sciences , vol.10 , Issue.1
    • Newport, E.L.1
  • 29
    • 0009445756 scopus 로고
    • Maturational constraints on language learning
    • E. L. Newport. 1990. Maturational constraints on language learning. Cognitive Science, 14(1).
    • (1990) Cognitive Science , vol.14 , Issue.1
    • Newport, E.L.1
  • 30
    • 80053382143 scopus 로고    scopus 로고
    • Coarse-to-fine syntactic machine translation using language projections
    • S. Petrov, A. Haghighi, and D. Klein. 2008. Coarse-to-fine syntactic machine translation using language projections. In Proc. of EMNLP.
    • (2008) Proc. of EMNLP
    • Petrov, S.1    Haghighi, A.2    Klein, D.3
  • 32
    • 84859916726 scopus 로고    scopus 로고
    • Minimized models for unsupervised part-of-speech tagging
    • S. Ravi and K. Knight. 2009. Minimized models for unsupervised part-of-speech tagging. In Proc. of ACL-IJCNLP.
    • (2009) Proc. of ACL-IJCNLP
    • Ravi, S.1    Knight, K.2
  • 33
    • 0032888001 scopus 로고    scopus 로고
    • Language acquisition in the absence of explicit negative evidence: How important is starting small?
    • D. L. T. Rohde and D. C. Plaut. 1999. Language acquisition in the absence of explicit negative evidence: How important is starting small? Cognition, 72(1).
    • (1999) Cognition , vol.72 , Issue.1
    • Rohde, D.L.T.1    Plaut, D.C.2
  • 35
    • 16244377091 scopus 로고    scopus 로고
    • Determining the number of clusters/segments in hierarchical clustering/segmentation algorithms
    • S. Salvador and P. Chan. 2004. Determining the number of clusters/segments in hierarchical clustering/segmentation algorithms. In Proc. of ICTAI.
    • (2004) Proc. of ICTAI
    • Salvador, S.1    Chan, P.2
  • 36
    • 0028443865 scopus 로고
    • Neural network learning control of robot manipulators using gradually increasing task difficulty
    • T. D. Sanger. 1994. Neural network learning control of robot manipulators using gradually increasing task difficulty. IEEE Trans. on Robotics and Automation, 10.
    • (1994) IEEE Trans. on Robotics and Automation , pp. 10
    • Sanger, T.D.1
  • 37
    • 0032286784 scopus 로고    scopus 로고
    • Shaping: The link between rats and robots
    • T. Savage. 1998. Shaping: The link between rats and robots. Connection Science, 10(3).
    • (1998) Connection Science , vol.10 , Issue.3
    • Savage, T.1
  • 38
    • 0035545047 scopus 로고    scopus 로고
    • Shaping: A multiple contingencies analysis and its relevance to behaviour-based robotics
    • T. Savage. 2001. Shaping: A multiple contingencies analysis and its relevance to behaviour-based robotics. Connection Science, 13(3).
    • (2001) Connection Science , vol.13 , Issue.3
    • Savage, T.1
  • 39
    • 80053271788 scopus 로고    scopus 로고
    • Fast unsupervised incremental parsing
    • Y. Seginer. 2007. Fast unsupervised incremental parsing. In Proc. of ACL.
    • (2007) Proc. of ACL
    • Seginer, Y.1
  • 40
    • 0001027894 scopus 로고
    • Transfer of learning by composing solutions of elemental squential tasks
    • S. P. Singh. 1992. Transfer of learning by composing solutions of elemental squential tasks. Machine Learning, 8.
    • (1992) Machine Learning , pp. 8
    • Singh, S.P.1
  • 42
    • 85149124789 scopus 로고    scopus 로고
    • Annealing techniques for unsupervised statistical language learning
    • N. A. Smith and J. Eisner. 2004. Annealing techniques for unsupervised statistical language learning. In Proc. of ACL.
    • (2004) Proc. of ACL
    • Smith, N.A.1    Eisner, J.2
  • 44
    • 84860514723 scopus 로고    scopus 로고
    • Annealing structural bias in multilingual weighted grammar induction
    • N. A. Smith and J. Eisner. 2006. Annealing structural bias in multilingual weighted grammar induction. In Proc. of COLING-ACL.
    • (2006) Proc. of COLING-ACL
    • Smith, N.A.1    Eisner, J.2
  • 45
    • 80053399428 scopus 로고    scopus 로고
    • An empirical study of semi-supervised structured conditional models for dependency parsing
    • J. Suzuki, H. Isozaki, X. Carreras, and M. Collins. 2009. An empirical study of semi-supervised structured conditional models for dependency parsing. In Proc. of EMNLP.
    • (2009) Proc. of EMNLP
    • Suzuki, J.1    Isozaki, H.2    Carreras, X.3    Collins, M.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.