메뉴 건너뛰기




Volumn 6, Issue 2, 2012, Pages

The latent maximum entropy principle

Author keywords

Expectation maximization; Information geometry; Iterative scaling; Latent variable models; Maximum entropy

Indexed keywords

EXPECTATION MAXIMIZATION; INFORMATION GEOMETRY; ITERATIVE SCALING; LATENT VARIABLE MODELS; MAXIMUM ENTROPY;

EID: 84866340966     PISSN: 15564681     EISSN: 1556472X     Source Type: Journal    
DOI: 10.1145/2297456.2297460     Document Type: Article
Times cited : (25)

References (52)
  • 1
    • 0001578518 scopus 로고
    • A learning algorithm for boltzmann machines
    • ACKLEY, D., HINTON, G., AND SEJNOWSKI, T. 1985. A learning algorithm for Boltzmann machines. Cognitive Sci. 9, 147-169.
    • (1985) Cognitive Sci. , vol.9 , pp. 147-169
    • Ackley, D.1    Hinton, G.2    Sejnowski, T.3
  • 2
    • 0029587111 scopus 로고
    • Information geometry of the EM and em algorithms for neural networks
    • DOI 10.1016/0893-6080(95)00003-8
    • AMARI, S. 1995. Information geometry of the EM and em algorithms for neural networks. Neural Netw. 8, 9, 1379-1408. (Pubitemid 26072898)
    • (1995) Neural Networks , vol.8 , Issue.9 , pp. 1379-1408
    • Amari, S.-I.1
  • 4
    • 0002652285 scopus 로고    scopus 로고
    • A maximum entropy approach to natural language processing
    • BERGER, A., DELLA PIETRA, S., AND DELLA PIETRA, V. 1996. A maximum entropy approach to natural language processing. Comput. Linguist. 22, 1, 39-71.
    • (1996) Comput. Linguist. , vol.22 , Issue.1 , pp. 39-71
    • Berger, A.1    Della Pietra, S.2    Della Pietra, V.3
  • 7
    • 0026898265 scopus 로고
    • Alternating minimization and boltzmann machine learning
    • BYRNE, W. 1992. Alternating minimization and Boltzmann machine learning. IEEE Trans. Neural Netw. 3, 4, 612-620.
    • (1992) IEEE Trans. Neural Netw. , vol.3 , Issue.4 , pp. 612-620
    • Byrne, W.1
  • 9
    • 0036643072 scopus 로고    scopus 로고
    • Logistic regression, AdaBoost and Bregman distances
    • DOI 10.1023/A:1013912006537
    • COLLINS, M., SCHAPIRE, R., AND SINGER, Y. 2002. Logistic regression, AdaBoost and Bregman distances. Mach. Learn. 48, 3, 253-285. (Pubitemid 34247580)
    • (2002) Machine Learning , vol.48 , Issue.1-3 , pp. 253-285
    • Collins, M.1    Schapire, R.E.2    Singer, Y.3
  • 11
    • 0000546609 scopus 로고
    • I-divergence geometry of probability distributions and minimization problems
    • CSISZAR, I. 1975. I-Divergence geometry of probability distributions and minimization problems. Ann. Probab. 3, 146-158.
    • (1975) Ann. Probab. , vol.3 , pp. 146-158
    • Csiszar, I.1
  • 12
    • 0001560954 scopus 로고
    • Information geometry and alternating minimization procedures
    • CSISZAR, I. AND TUSNADY, G. 1984. Information geometry and alternating minimization procedures. Statistics and Decisions. Supplement Issue 1, 205-237.
    • (1984) Statistics and Decisions. Supplement , vol.1 , pp. 205-237
    • Csiszar, I.1    Tusnady, G.2
  • 13
    • 0001573124 scopus 로고
    • Generalized iterative scaling for log-linear models
    • DARROCH, J. AND RATCHLIFF, D. 1972. Generalized iterative scaling for log-linear models. Ann. Math. Stat. 43, 5, 1470-1480.
    • (1972) Ann. Math. Stat. , vol.43 , Issue.5 , pp. 1470-1480
    • Darroch, J.1    Ratchliff, D.2
  • 15
    • 0002629270 scopus 로고
    • Maximum likelihood estimation from incomplete data via the em algorithm
    • DEMPSTER, A., LAIRD, N., AND RUBIN, D. 1977. Maximum likelihood estimation from incomplete data via the EM algorithm. J. Royal Stat. Soc. Series B, 39, 1-38.
    • (1977) J. Royal Stat. Soc. Series B , vol.39 , pp. 1-38
    • Dempster, A.1    Laird, N.2    Rubin, D.3
  • 18
    • 0000764772 scopus 로고
    • The use of multiple measurements in taxonomic problems
    • FISHER, R. 1936. The use of multiple measurements in taxonomic problems. Ann. Eugenics 7, II, 179-188.
    • (1936) Ann. Eugenics , vol.7 , Issue.2 , pp. 179-188
    • Fisher, R.1
  • 19
    • 77956929686 scopus 로고    scopus 로고
    • Posterior regularization for structured latent variable models
    • GANCHEV, K., GRAFIA, J., GILLENWATER, J., AND TASKAR, B. 2010. Posterior regularization for structured latent variable models. J. Mach. Learn. Res. 11, 2001-2049.
    • (2010) J. Mach. Learn. Res. , vol.11 , pp. 2001-2049
    • Ganchev, K.1    Grafia, J.2    Gillenwater, J.3    Taskar, B.4
  • 20
    • 0028419019 scopus 로고
    • Maximum a posteriori estimation for multivariate gaussian mixture observations of markov chains
    • GAUVAIN, J. AND LEE, C.-H. 1994. Maximum a posteriori estimation for multivariate Gaussian mixture observations of Markov chains. IEEE Trans. Speech Audio Process. 2, 2, 291-298.
    • (1994) IEEE Trans. Speech Audio Process. , vol.2 , Issue.2 , pp. 291-298
    • Gauvain, J.1    Lee, C.-H.2
  • 25
    • 0034818212 scopus 로고    scopus 로고
    • Unsupervised learning by probabilistic Latent Semantic Analysis
    • DOI 10.1023/A:1007617005950
    • HOFMANN, T. 2001. Unsupervised learning by probabilistic latent semantic analysis. Mach. Learn. 42, 1, 177-196. (Pubitemid 32872403)
    • (2001) Machine Learning , vol.42 , Issue.1-2 , pp. 177-196
    • Hofmann, T.1
  • 26
    • 77949528697 scopus 로고    scopus 로고
    • Iterative scaling and coordinate descent methods for maximum entropy models
    • HUANG, F., HSIEH, C., CHANG, K., AND LIN, C. 2010. Iterative scaling and coordinate descent methods for maximum entropy models. J. Mach. Learn. Res. 11, 815-848.
    • (2010) J. Mach. Learn. Res. , vol.11 , pp. 815-848
    • Huang, F.1    Hsieh, C.2    Chang, K.3    Lin, C.4
  • 33
    • 58149210716 scopus 로고
    • The em-algorithm for graphical association models with missing data
    • LAURITZEN, S. 1995. The EM-algorithm for graphical association models with missing data. Comput. Stat. Data Anal.19, 2, 191-201.
    • (1995) Comput. Stat. Data Anal. , vol.19 , Issue.2 , pp. 191-201
    • Lauritzen, S.1
  • 36
    • 84974288913 scopus 로고
    • A hierarchical dirichlet language model
    • MACKAY, D. AND PETO, L. 1995. A hierarchical Dirichlet language model. Natural Lang. Eng. 1, 3, 289-307.
    • (1995) Natural Lang Eng , vol.1 , Issue.3 , pp. 289-307
    • Mackay, D.1    Peto, L.2
  • 38
    • 0000251971 scopus 로고
    • Maximum likelihood estimation via the ecl algorithm: A general framework
    • MENG, X. AND RUBIN, D. 1993. Maximum likelihood estimation via the ECL algorithm: A general framework. Biometrika 80, 2, 267-278.
    • (1993) Biometrika , vol.80 , Issue.2 , pp. 267-278
    • Meng, X.1    Rubin, D.2
  • 42
    • 0030181951 scopus 로고    scopus 로고
    • A maximum entropy approach to adaptive statistical language modeling
    • ROSENFELD, R. 1996. A maximum entropy approach to adaptive statistical language modeling. Comput. Speech Lang. 10, 2, 187-228.
    • (1996) Comput. Speech Lang. , vol.10 , Issue.2 , pp. 187-228
    • Rosenfeld, R.1
  • 43
    • 0037516827 scopus 로고    scopus 로고
    • Tree-based reparameterization framework for analysis of belief propagation and related algorithms
    • WAINWRIGHT, M., JAAKKOLA, T., AND WILLSKY, A. 2003. Tree-based reparameterization framework for analysis of belief propagation and related algorithms. IEEE Trans. Inf. Theory 49, 5, 1120-1146.
    • (2003) IEEE Trans. Inf. Theory , vol.49 , Issue.5 , pp. 1120-1146
    • Wainwright, M.1    Jaakkola, T.2    Willsky, A.3
  • 47
    • 24044495247 scopus 로고    scopus 로고
    • Combining statistical language models via the latent maximum entropy principle
    • DOI 10.1007/s10994-005-0928-7
    • WANG, S., SCHUURMANS, D., PENG, F., AND ZHAO, Y. 2005. Combining statistical language models via the latent maximum entropy principle. Mach. Learn. J. 60 (Special Issue on Learning in Speech and Language Technologies), 229-250. (Pubitemid 41218069)
    • (2005) Machine Learning , vol.60 , Issue.1-3 , pp. 229-250
    • Wang, S.1    Schuurmans, D.2    Peng, F.3    Zhao, Y.4
  • 49
    • 0002210265 scopus 로고
    • On the convergence properties of the em algorithm
    • WU, C. 1983. On the convergence properties of the EM algorithm. Ann. Stat. 11, 95-103.
    • (1983) Ann. Stat. , vol.11 , pp. 95-103
    • Wu, C.1
  • 50
    • 23744513375 scopus 로고    scopus 로고
    • Constructing free-energy approximations and generalized belief propagation algorithms
    • DOI 10.1109/TIT.2005.850085
    • YEDIDIA, J., FREEMAN, W., AND WEISS, Y. 2005. Constructing free energy approximations and generalized belief propagation algorithms. IEEE Trans. Inf. Theory 51, 7, 2282-2312. (Pubitemid 41136394)
    • (2005) IEEE Transactions on Information Theory , vol.51 , Issue.7 , pp. 2282-2312
    • Yedidia, J.S.1    Freeman, W.T.2    Weiss, Y.3
  • 52
    • 73549086344 scopus 로고    scopus 로고
    • Maximum entropy discrimination markov networks
    • ZHU, J. AND XING, E. 2009. Maximum entropy discrimination Markov networks. J. Mach. Learn. Res. 10, 2531-2569.
    • (2009) J. Mach. Learn. Res. , vol.10 , pp. 2531-2569
    • Zhu, J.1    Xing, E.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.