메뉴 건너뛰기




Volumn , Issue , 2010, Pages 172-181

Improved natural language learning via variance-regularization support vector machines

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING RATES; LEXICAL DISAMBIGUATION; NATURAL LANGUAGE LEARNING; QUADRATIC FUNCTION; TRAINING EXAMPLE;

EID: 84862273336     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (9)

References (47)
  • 1
    • 33750729556 scopus 로고    scopus 로고
    • Manifold regularization: A geometric frame work for learning from labeled and unlabeled exam ples
    • Mikhail Belkin, Partha Niyogi, and Vikas Sindhwani. 2006. Manifold regularization: A geometric frame work for learning from labeled and unlabeled exam ples. JMLR, 7:2399-2434.
    • (2006) JMLR , vol.7 , pp. 2399-2434
    • Belkin, M.1    Niyogi, P.2    Sindhwani, V.3
  • 2
    • 84859913623 scopus 로고    scopus 로고
    • Distributional identification of non-referential pronouns
    • Shane Bergsma, Dekang Lin, and Randy Goebel. 2008. Distributional identification of non-referential pronouns. In ACL-08: HLT.
    • (2008) ACL-08: HLT
    • Bergsma, S.1    Lin, D.2    Goebel, R.3
  • 3
    • 78649231706 scopus 로고    scopus 로고
    • Web-scale N-gram models for lexical disam biguation
    • Shane Bergsma, Dekang Lin, and Randy Goebel. 2009. Web-scale N-gram models for lexical disam biguation. In IJCAI.
    • (2009) IJCAI
    • Bergsma, S.1    Lin, D.2    Goebel, R.3
  • 4
    • 84860524227 scopus 로고    scopus 로고
    • Biographies, bollywood, boom-boxes and blenders: Domain adaptation for sentiment classi fication
    • John Blitzer, Mark Dredze, and Fernando Pereira. 2007. Biographies, bollywood, boom-boxes and blenders: Domain adaptation for sentiment classi fication. In ACL.
    • (2007) ACL
    • Blitzer, J.1    Dredze, M.2    Pereira, F.3
  • 5
    • 0031620208 scopus 로고    scopus 로고
    • Combining labeled and unlabeled data with co-training
    • Avrim Blum and Tom Mitchell. 1998. Combining labeled and unlabeled data with co-training. In COLT.
    • (1998) COLT
    • Blum, A.1    Mitchell, T.2
  • 8
    • 77954618708 scopus 로고    scopus 로고
    • Compressing trigram language models with Golomb coding
    • Kenneth Church, Ted Hart, and Jianfeng Gao. 2007. Compressing trigram language models with Golomb coding. In EMNLP-CoNLL.
    • (2007) EMNLP-CoNLL
    • Church, K.1    Hart, T.2    Gao, J.3
  • 9
    • 0028424239 scopus 로고
    • Improving generalization with active learning
    • David Cohn, Les Atlas, and Richard Ladner. 1994. Improving generalization with active learning. Mach. Learn., 15(2):201-221.
    • (1994) Mach. Learn , vol.15 , Issue.2 , pp. 201-221
    • Cohn, D.1    Atlas, L.2    Ladner, R.3
  • 10
    • 34249753618 scopus 로고
    • Support-vector networks
    • Corinna Cortes and Vladimir Vapnik. 1995. Support-vector networks. Mach. Learn., 20(3):273-297.
    • (1995) Mach. Learn , vol.20 , Issue.3 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 11
    • 84862270856 scopus 로고    scopus 로고
    • CPLEX, IBM ILOG CPLEX 9.1
    • CPLEX. 2005. IBM ILOG CPLEX 9.1. www.ilog.com/products/cplex/.
    • (2005)
  • 12
    • 0010442827 scopus 로고    scopus 로고
    • On the algorithmic implementation of multiclass kernel-based vector machines
    • Koby Crammer and Yoram Singer. 2001. On the algorithmic implementation of multiclass kernel-based vector machines. JMLR, 2:265-292.
    • (2001) JMLR , vol.2 , pp. 265-292
    • Crammer, K.1    Singer, Y.2
  • 13
    • 0141496132 scopus 로고    scopus 로고
    • Ultracon-servative online algorithms for multiclass problems
    • Koby Crammer and Yoram Singer. 2003. Ultracon-servative online algorithms for multiclass problems. JMLR, 3:951-991.
    • (2003) JMLR , vol.3 , pp. 951-991
    • Crammer, K.1    Singer, Y.2
  • 15
    • 84860513476 scopus 로고    scopus 로고
    • Frustratingly easy domain adaptation
    • Hal III Daumé. 2007. Frustratingly easy domain adaptation. In ACL.
    • (2007) ACL
    • Daumé, H.1
  • 16
    • 56449101965 scopus 로고    scopus 로고
    • Confidence-weighted linear classification
    • Mark Dredze, Koby Crammer, and Fernando Pereira. 2008. Confidence-weighted linear classification. In ICML.
    • (2008) ICML
    • Dredze, M.1    Crammer, K.2    Pereira, F.3
  • 18
    • 50949133669 scopus 로고    scopus 로고
    • LIBLIN-EAR: A library for large linear classification
    • Rong-En Fan, Kai-Wei Chang, Cho-Jui Hsieh, Xiang-Rui Wang, and Chih-Jen Lin. 2008. LIBLIN-EAR: A library for large linear classification. JMLR, 9:1871-1874.
    • (2008) JMLR , vol.9 , pp. 1871-1874
    • Fan, R.-E.1    Chang, K.-W.2    Hsieh, C.-J.3    Wang, X.-R.4    Lin, C.-J.5
  • 19
    • 0032662978 scopus 로고    scopus 로고
    • A Winnow-based approach to context-sensitive spelling correction
    • Andrew R. Golding and Dan Roth. 1999. A Winnow-based approach to context-sensitive spelling correction. Mach. Learn., 34(1-3):107-130.
    • (1999) Mach. Learn , vol.34 , Issue.1-3 , pp. 107-130
    • Golding, A.R.1    Roth, D.2
  • 20
    • 84898960512 scopus 로고    scopus 로고
    • Constraint classification for multiclass classification and ranking
    • Sariel Har-Peled, Dan Roth, and Dav Zimak. 2003. Constraint classification for multiclass classification and ranking. In NIPS.
    • (2003) NIPS
    • Har-Peled, S.1    Roth, D.2    Zimak, D.3
  • 21
    • 17644371642 scopus 로고    scopus 로고
    • Correcting real-word spelling errors by restoring lexical cohesion
    • Graeme Hirst and Alexander Budanitsky. 2005. Correcting real-word spelling errors by restoring lexical cohesion. Nat. Lang. Eng., 11(1):87-111.
    • (2005) Nat. Lang. Eng , vol.11 , Issue.1 , pp. 87-111
    • Hirst, G.1    Budanitsky, A.2
  • 22
    • 0036505670 scopus 로고    scopus 로고
    • A comparison of methods for multiclass support vector machines
    • Chih-Wei Hsu and Chih-Jen Lin. 2002. A comparison of methods for multiclass support vector machines. IEEE Trans. Neur. Networks, 13(2):415-425.
    • (2002) IEEE Trans. Neur. Networks , vol.13 , Issue.2 , pp. 415-425
    • Hsu, C.-W.1    Lin, C.-J.2
  • 23
    • 69549111057 scopus 로고    scopus 로고
    • Cutting-plane training of structural SVMs
    • Thorsten Joachims, Thomas Finley, and Chun-Nam John Yu. 2009. Cutting-plane training of structural SVMs. Mach. Learn., 77(1):27-59.
    • (2009) Mach. Learn , vol.77 , Issue.1 , pp. 27-59
    • Joachims, T.1    Finley, T.2    Yu, J.C.-N.3
  • 24
    • 0242456822 scopus 로고    scopus 로고
    • Optimizing search engines using clickthrough data
    • Thorsten Joachims. 2002. Optimizing search engines using clickthrough data. In KDD.
    • (2002) KDD
    • Joachims, T.1
  • 25
    • 33749563073 scopus 로고    scopus 로고
    • Training linear SVMs in linear time
    • Thorsten Joachims. 2006. Training linear SVMs in linear time. In KDD.
    • (2006) KDD
    • Joachims, T.1
  • 26
    • 80053551637 scopus 로고    scopus 로고
    • Simple semi-supervised dependency parsing
    • Terry Koo, Xavier Carreras, and Michael Collins. 2008. Simple semi-supervised dependency parsing. In ACL-08: HLT.
    • (2008) ACL-08: HLT
    • Koo, T.1    Carreras, X.2    Collins, M.3
  • 27
    • 58649122677 scopus 로고    scopus 로고
    • Novel multiclass classifiers based on the min imization of the within-class variance
    • Irene Kotsia, Stefanos Zafeiriou, and Ioannis Pitas. 2009. Novel multiclass classifiers based on the min imization of the within-class variance. IEEE Trans. Neur. Networks, 20(1):14-34.
    • (2009) IEEE Trans. Neur. Networks , vol.20 , Issue.1 , pp. 14-34
    • Kotsia, I.1    Zafeiriou, S.2    Pitas, I.3
  • 30
    • 85117730830 scopus 로고    scopus 로고
    • Name tagging with word clusters and discriminative training
    • Scott Miller, Jethran Guinness, and Alex Zamanian. 2004. Name tagging with word clusters and discriminative training. In HLT-NAACL.
    • (2004) HLT-NAACL
    • Miller, S.1    Guinness, J.2    Zamanian, A.3
  • 31
    • 59549087165 scopus 로고    scopus 로고
    • Discriminative vs. generative classifiers: A comparison of logistic regression and naive bayes
    • Andrew Y. Ng and Michael I. Jordan. 2002. Discriminative vs. generative classifiers: A comparison of logistic regression and naive bayes. In NIPS.
    • (2002) NIPS
    • Ng, A.Y.1    Jordan, M.I.2
  • 32
    • 77749246824 scopus 로고    scopus 로고
    • Graph-cut-based anaphoricity determination for coreference resolution
    • Vincent NG. 2009. Graph-cut-based anaphoricity determination for coreference resolution. In NAACL-HLT.
    • (2009) NAACL-HLT
    • Vincent, N.G.1
  • 33
    • 85101305674 scopus 로고    scopus 로고
    • Discriminative training and maximum entropy models for statistical machine translation
    • Franz J. Och and Hermann Ney. 2002. Discriminative training and maximum entropy models for statistical machine translation. In ACL.
    • (2002) ACL
    • Och, F.J.1    Ney, H.2
  • 34
    • 80053344834 scopus 로고    scopus 로고
    • A discriminative language model with pseudo-negative samples
    • Daisuke Okanohara and Jun'ichi Tsujii. 2007. A discriminative language model with pseudo-negative samples. In ACL.
    • (2007) ACL
    • Okanohara, D.1    Tsujii, J.2
  • 35
    • 0242306667 scopus 로고
    • Towards the automatic recognition of anaphoric features in English text: The impersonal pronoun it
    • Chris D. Paice and Gareth D. Husk. 1987. Towards the automatic recognition of anaphoric features in English text: the impersonal pronoun "it". Computer Speech and Language, 2:109-132.
    • (1987) Computer Speech and Language , vol.2 , pp. 109-132
    • Paice, C.D.1    Husk, G.D.2
  • 36
    • 33749240383 scopus 로고    scopus 로고
    • Constructing informative priors using transfer learning
    • Rajat Raina, Andrew Y. NG, and Daphne Koller. 2006. Constructing informative priors using transfer learning. In ICML.
    • (2006) ICML
    • Raina, R.1    Andrew, Y.N.G.2    Koller, D.3
  • 37
    • 56749117943 scopus 로고    scopus 로고
    • In defense of one-vs-all classification
    • Ryan Rifkin and Aldebaro Klautau. 2004. In defense of one-vs-all classification. JMLR, 5:101-141.
    • (2004) JMLR , vol.5 , pp. 101-141
    • Rifkin, R.1    Klautau, A.2
  • 38
    • 84859905260 scopus 로고    scopus 로고
    • Contrastive estimation: Training log-linear models on unlabeled data
    • Noah A. Smith and Jason Eisner. 2005. Contrastive estimation: training log-linear models on unlabeled data. In ACL.
    • (2005) ACL
    • Smith, N.A.1    Eisner, J.2
  • 39
    • 0035394251 scopus 로고    scopus 로고
    • Using support vector machines to enhance the performance of elastic graph matching for frontal face authentication
    • Anastasios Tefas, Constantine Kotropoulos, and Ioan-nis Pitas. 2001. Using support vector machines to enhance the performance of elastic graph matching for frontal face authentication. IEEE Trans. Pattern Anal. Machine Intell., 23:735-746.
    • (2001) IEEE Trans. Pattern Anal. Machine Intell , vol.23 , pp. 735-746
    • Tefas, A.1    Kotropoulos, C.2    Pitas, I.-N.3
  • 40
    • 78651280222 scopus 로고    scopus 로고
    • The ups and downs of preposition error detection in ESL writing
    • Joel R. Tetreault and Martin Chodorow. 2008. The ups and downs of preposition error detection in ESL writing. In COLING.
    • (2008) COLING
    • Tetreault, J.R.1    Chodorow, M.2
  • 41
    • 0042868698 scopus 로고    scopus 로고
    • Support vector machine active learning with applications to text classification
    • Simon Tong and Daphne Koller. 2002. Support vector machine active learning with applications to text classification. JMLR, 2:45-66.
    • (2002) JMLR , vol.2 , pp. 45-66
    • Tong, S.1    Koller, D.2
  • 42
    • 24944537843 scopus 로고    scopus 로고
    • Large margin methods for structured and interdependent output variables
    • Ioannis Tsochantaridis, Thorsten Joachims, Thomas Hofmann, and Yasemin Altun. 2005. Large margin methods for structured and interdependent output variables. JMLR, 6:1453-1484.
    • (2005) JMLR , vol.6 , pp. 1453-1484
    • Tsochantaridis, I.1    Joachims, T.2    Hofmann, T.3    Altun, Y.4
  • 44
    • 84859884130 scopus 로고    scopus 로고
    • Improved large margin dependency parsing via local constraints and Laplacian regularization
    • Qin Iris Wang, Colin Cherry, Dan Lizotte, and Dale Schuurmans. 2006. Improved large margin dependency parsing via local constraints and Laplacian regularization. In CoNLL.
    • (2006) CoNLL
    • Wang, Q.I.1    Cherry, C.2    Lizotte, D.3    Schuurmans, D.4
  • 45
    • 0003425673 scopus 로고    scopus 로고
    • Multi-class Support Vector Machines
    • Department of Computer Science, Royal Holloway, University of London
    • Jason Weston and Chris Watkins. 1998. Multi-class support vector machines. Technical Report CSD-TR-98-04, Department of Computer Science, Royal Holloway, University of London.
    • (1998) Technical Report CSD-TR-98-04
    • Weston, J.1    Watkins, C.2
  • 46
    • 85141919230 scopus 로고
    • Unsupervised word sense disambiguation rivaling supervised methods
    • David Yarowsky. 1995. Unsupervised word sense disambiguation rivaling supervised methods. In ACL.
    • (1995) ACL
    • Yarowsky, D.1
  • 47
    • 77957858975 scopus 로고    scopus 로고
    • Using "annotator rationales" to improve machine learning for text categorization
    • Omar Zaidan, Jason Eisner, and Christine Piatko. 2007. Using "annotator rationales" to improve machine learning for text categorization. In NAACL-HLT.
    • (2007) NAACL-HLT
    • Zaidan, O.1    Eisner, J.2    Piatko, C.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.