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Volumn 47, Issue , 2013, Pages 157-203

A survey on latent tree models and applications

Author keywords

[No Author keywords available]

Indexed keywords

ELECTRONICS ENGINEERING;

EID: 84879912869     PISSN: None     EISSN: 10769757     Source Type: Journal    
DOI: 10.1613/jair.3879     Document Type: Review
Times cited : (73)

References (80)
  • 4
    • 0001656793 scopus 로고    scopus 로고
    • The performance of neighbor-joining methods of phylogenetic reconstruction
    • Atteson, K. (1999). The performance of neighbor-joining methods of phylogenetic reconstruction. Algorithmica, 25(2), 251-278. (Pubitemid 129674400)
    • (1999) Algorithmica (New York) , vol.25 , Issue.2-3 , pp. 251-278
    • Atteson, K.1
  • 6
    • 13444269543 scopus 로고    scopus 로고
    • Haploview: Analysis and visualization of LD and haplotype maps
    • DOI 10.1093/bioinformatics/bth457
    • Barrett, J. C., Fry, B., Maller, J., & Daly, M. J. (2005). Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics, 21(2), 263-265. (Pubitemid 40202029)
    • (2005) Bioinformatics , vol.21 , Issue.2 , pp. 263-265
    • Barrett, J.C.1    Fry, B.2    Maller, J.3    Daly, M.J.4
  • 7
    • 0031273462 scopus 로고    scopus 로고
    • Adaptive probabilistic networks with hidden variables
    • Binder, J., Koller, D., Russel, S., & Kanazawa, K. (1997). Adaptive probabilistic networks with hidden variables. Machine Learning, 29(2-3), 213-244. (Pubitemid 127510039)
    • (1997) Machine Learning , vol.29 , Issue.2-3 , pp. 213-244
    • Binder, J.1    Koller, D.2    Russell, S.3    Kanazawa, K.4
  • 8
    • 0018002532 scopus 로고
    • Taxonomy with confidence
    • DOI 10.1016/0025-5564(78)90089-5
    • Cavender, J. A. (1978). Taxonomy with confidence. Mathematical Biosciences, 40(3-4), 271-280. (Pubitemid 9045615)
    • (1978) Mathematical Biosciences , vol.40 , Issue.3-4 , pp. 271-280
    • Cavender, J.A.1
  • 10
    • 80955168976 scopus 로고    scopus 로고
    • Ph.D. thesis, The Hong Kong University of Science and Technology
    • Chen, T. (2008). Search-based learning of latent tree models. Ph.D. thesis, The Hong Kong University of Science and Technology.
    • (2008) Search-based Learning of Latent Tree Models
    • Chen, T.1
  • 11
    • 80054122982 scopus 로고    scopus 로고
    • Model-based multidimensional clustering of categorical data
    • Chen, T., Zhang, N. L., Liu, T., Poon, K. M., & Wang, Y. (2012). Model-based multidimensional clustering of categorical data. Artificial Intelligence, 176(1), 2246-2269.
    • (2012) Artificial Intelligence , vol.176 , Issue.1 , pp. 2246-2269
    • Chen, T.1    Zhang, N.L.2    Liu, T.3    Poon, K.M.4    Wang, Y.5
  • 13
    • 0031272327 scopus 로고    scopus 로고
    • Efficient approximations for the marginal likelihood of bayesian networks with hidden variables
    • Chickering, D. M., & Heckerman, D. (1997). Efficient approximations for the marginal likelihood of Bayesian networks with hidden variables. Machine Learning, 29(2-3), 181-212. (Pubitemid 127510038)
    • (1997) Machine Learning , vol.29 , Issue.2-3 , pp. 181-212
    • Chickering, D.M.1    Heckerman, D.2
  • 15
    • 84933530882 scopus 로고
    • Approximating discrete probability distributions with dependence trees
    • Chow, C. K., & Liu, C. N. (1968). Approximating discrete probability distributions with dependence trees. IEEE Transactions on Information Theory, 14(3), 462-467.
    • (1968) IEEE Transactions on Information Theory , vol.14 , Issue.3 , pp. 462-467
    • Chow, C.K.1    Liu, C.N.2
  • 16
    • 0025401005 scopus 로고
    • The computational complexity of probabilistic inference using Bayesian belief networks
    • Cooper, G. F. (1990). The computational complexity of probabilistic inference using Bayesian belief networks. Artificial Intelligence, 42(2-3), 393-405.
    • (1990) Artificial Intelligence , vol.42 , Issue.2-3 , pp. 393-405
    • Cooper, G.F.1
  • 18
    • 79952002699 scopus 로고    scopus 로고
    • Evolutionary trees and the Ising model on the Bethe lattice: A proof of Steel's conjecture
    • Daskalakis, C., Mossel, E., & Roch, S. (2009). Evolutionary trees and the Ising model on the Bethe lattice: A proof of Steel's conjecture. Probability Theory and Related Fields, 149(1-2), 149-189.
    • (2009) Probability Theory and Related Fields , vol.149 , Issue.1-2 , pp. 149-189
    • Daskalakis, C.1    Mossel, E.2    Roch, S.3
  • 21
    • 0001860411 scopus 로고    scopus 로고
    • A few logs suffice to build (almost) all trees: Part II
    • PII S0304397599000286
    • Erdos, P. L., Szekely, L. A., Steel, M. A., & Warnow, T. J. (1999). A few logs suffice to build (almost) all trees: Part II. Theoretical Computer Science, 221(1-2), 77-118. (Pubitemid 129608962)
    • (1999) Theoretical Computer Science , vol.221 , Issue.1-2 , pp. 77-118
    • Erdos, P.L.1    Steel, M.A.2    Szekely, L.A.3    Warnow, T.J.4
  • 23
    • 84959807796 scopus 로고
    • A probability model for inferring evolutionary trees
    • Farris, J. S. (1973). A probability model for inferring evolutionary trees. Systematic Zoology, 22(3), 250-256.
    • (1973) Systematic Zoology , vol.22 , Issue.3 , pp. 250-256
    • Farris, J.S.1
  • 25
    • 0036110773 scopus 로고    scopus 로고
    • A structural EM algorithm for phylogenetic inference
    • DOI 10.1089/10665270252935494
    • Friedman, N., Ninio, M., Pe'er, I., & Pupko, T. (2002). A structural EM algorithm for phylogenetic inference. Journal of Computational Biology, 9(2), 331-353. (Pubitemid 34548268)
    • (2002) Journal of Computational Biology , vol.9 , Issue.2 , pp. 331-353
    • Friedman, N.1    Ninio, M.2    Pe'er, I.3    Pupko, T.4
  • 26
    • 0031276011 scopus 로고    scopus 로고
    • Bayesian Network Classifiers
    • Friedman, N., Geiger, D., & Goldszmidt, M. (1997). Bayesian network classifiers. Machine Learning, 29(2-3), 131-163. (Pubitemid 127510036)
    • (1997) Machine Learning , vol.29 , Issue.2-3 , pp. 131-163
    • Friedman, N.1    Geiger, D.2    Goldszmidt, M.3
  • 27
    • 33749540417 scopus 로고    scopus 로고
    • Neighbor-joining revealed
    • DOI 10.1093/molbev/msl072
    • Gascuel, O., & Steel, M. (2006). Neighbor-joining revealed. Molecular Biology and Evolu-tion, 23(11), 1997-2000. (Pubitemid 44536808)
    • (2006) Molecular Biology and Evolution , vol.23 , Issue.11 , pp. 1997-2000
    • Gascuel, O.1    Steel, M.2
  • 38
    • 0030419236 scopus 로고    scopus 로고
    • Using hidden nodes in Bayesian networks
    • PII S0004370295001190
    • Kwoh, C.-K., & Gillies, D. F. (1996). Using hidden nodes in Bayesian networks. Artificial Intelligence, 88(1-2), 1-38. (Pubitemid 126371536)
    • (1996) Artificial Intelligence , vol.88 , Issue.1-2 , pp. 1-38
    • Kwoh, C.-K.1    Gillies, D.F.2
  • 40
    • 67649392255 scopus 로고    scopus 로고
    • Latent classification models for binary data
    • Langseth, H., & Nielsen, T. D. (2009). Latent classification models for binary data. Pattern Recognition, 42(11), 2724-2736.
    • (2009) Pattern Recognition , vol.42 , Issue.11 , pp. 2724-2736
    • Langseth, H.1    Nielsen, T.D.2
  • 41
    • 58149210716 scopus 로고
    • The em algorithm for graphical association models with missing data
    • Lauritzen, S. L. (1995). The EM algorithm for graphical association models with missing data. Computational Statistics & Data Analysis, 19(2), 191-201.
    • (1995) Computational Statistics & Data Analysis , vol.19 , Issue.2 , pp. 191-201
    • Lauritzen, S.L.1
  • 45
    • 0004089936 scopus 로고
    • Discrete factor analysis: Learning hidden variables in Bayesian network
    • University of Pittsburgh
    • Martin, J., & Vanlehn, K. (1995). Discrete factor analysis: Learning hidden variables in Bayesian network. Tech. rep., Department of Computer Science, University of Pittsburgh.
    • (1995) Tech. Rep., Department of Computer Science
    • Martin, J.1    Vanlehn, K.2
  • 46
    • 0034676518 scopus 로고    scopus 로고
    • Using a Bayesian belief network to aid differential diagnosis of tropical bovine diseases
    • McKendrick, I. J., Gettinbya, G., Gua, Y., Reidb, S. W. J., & Revie, C. W. (2000). Using a Bayesian belief network to aid differential diagnosis of tropical bovine diseases. Preventive Veterinary Medicine, 47(3), 141-156.
    • (2000) Preventive Veterinary Medicine , vol.47 , Issue.3 , pp. 141-156
    • McKendrick, I.J.1    Gettinbya, G.2    Gua, Y.3    Reidb, S.W.J.4    Revie, C.W.5
  • 47
    • 33746918412 scopus 로고    scopus 로고
    • Learning nonsingular phylogenies and hidden Markov models
    • DOI 10.1214/105051606000000024
    • Mossel, E., & Roch, S. (2006). Learning nonsingular phylogenies and hiddenMarkov models. The Annals of Applied Probability, 16(2), 583-614. (Pubitemid 44196526)
    • (2006) Annals of Applied Probability , vol.16 , Issue.2 , pp. 583-614
    • Mossel, E.1    Roch, S.2
  • 49
    • 83255192917 scopus 로고    scopus 로고
    • Visualization of pairwise and multilocus linkage disequilibrium structure using latent forests
    • Mourad, R., Sinoquet, C., Dina, C., & Leray, P. (2011). Visualization of pairwise and multilocus linkage disequilibrium structure using latent forests. PLoS ONE, 6(12), e27320.
    • (2011) PLoS ONE , vol.6 , Issue.12
    • Mourad, R.1    Sinoquet, C.2    Dina, C.3    Leray, P.4
  • 50
    • 78651241266 scopus 로고    scopus 로고
    • A hierarchical Bayesian network approach for linkage disequilibrium modeling and data-dimensionality reduction prior to genomewide association studies
    • Mourad, R., Sinoquet, C., & Leray, P. (2011). A hierarchical Bayesian network approach for linkage disequilibrium modeling and data-dimensionality reduction prior to genomewide association studies. BMC Bioinformatics, 12, 16.
    • (2011) BMC Bioinformatics , vol.12 , pp. 16
    • Mourad, R.1    Sinoquet, C.2    Leray, P.3
  • 53
    • 0001473437 scopus 로고
    • On estimation of a probability density function and mode
    • Parzen, E. (1962). On estimation of a probability density function and mode. Annals of Mathematical Statistics, 33, 1065-1076.
    • (1962) Annals of Mathematical Statistics , vol.33 , pp. 1065-1076
    • Parzen, E.1
  • 56
    • 84911584312 scopus 로고
    • Shortest connection networks and some generalizations
    • Prim, R. C. (1957). Shortest connection networks and some generalizations. Bell System Technical Journal, 36, 1389-1401.
    • (1957) Bell System Technical Journal , vol.36 , pp. 1389-1401
    • Prim, R.C.1
  • 57
    • 84936421967 scopus 로고
    • Choosing models for cross-classifications
    • Raftery, A. E. (1986). Choosing models for cross-classifications. American Sociological Review, 51(1), 145-146.
    • (1986) American Sociological Review , vol.51 , Issue.1 , pp. 145-146
    • Raftery, A.E.1
  • 58
    • 0001529784 scopus 로고
    • Remarks on some nonparametric estimates of a density function
    • Rosenblatt, M. (1956). Remarks on some nonparametric estimates of a density function. Annals of Mathematical Statistics, 27, 832-837.
    • (1956) Annals of Mathematical Statistics , vol.27 , pp. 832-837
    • Rosenblatt, M.1
  • 59
    • 0023375195 scopus 로고
    • The neighbor-joining method: A new method for reconstructing phylogenetic trees
    • Saitou, N., & Nei, M. (1987). The neighbor-joining method: A new method for reconstructing phylogenetic trees. Molecular Biology and Evolution, 4(4), 406-425.
    • (1987) Molecular Biology and Evolution , vol.4 , Issue.4 , pp. 406-425
    • Saitou, N.1    Nei, M.2
  • 60
    • 0000120766 scopus 로고
    • Estimating the dimension of a model
    • Schwartz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6(2), 461-464.
    • (1978) The Annals of Statistics , vol.6 , Issue.2 , pp. 461-464
    • Schwartz, G.1
  • 62
    • 67149095078 scopus 로고    scopus 로고
    • Designing genome-wide association studies: Sample size, power, imputation, and the choice of genotyping chip
    • Spencer, C. C., Su, Z., Donnelly, P., & Marchini, J. (2009). Designing genome-wide association studies: sample size, power, imputation, and the choice of genotyping chip. PLoS Genetics, 5(5), e1000477.
    • (2009) PLoS Genetics , vol.5 , Issue.5
    • Spencer, C.C.1    Su, Z.2    Donnelly, P.3    Marchini, J.4
  • 63
  • 64
    • 52449147252 scopus 로고
    • The complexity of reconstructing trees from qualitative characters and subtrees
    • Steel, M. (1992). The complexity of reconstructing trees from qualitative characters and subtrees. Journal of Classification, 9(1), 91-116.
    • (1992) Journal of Classification , vol.9 , Issue.1 , pp. 91-116
    • Steel, M.1
  • 65
    • 79960151222 scopus 로고    scopus 로고
    • Learning high-dimensional Markov forest distributions: Analysis of error rates
    • Tan, V. Y. F., Anandkumar, A., & Willsky, A. (2011). Learning high-dimensional Markov forest distributions: Analysis of error rates. Journal of Machine Learning Research, 12, 1617-1653.
    • (2011) Journal of Machine Learning Research , vol.12 , pp. 1617-1653
    • Tan, V.Y.F.1    Anandkumar, A.2    Willsky, A.3
  • 66
    • 35348983887 scopus 로고    scopus 로고
    • A second generation human haplotype map of over 3.1 million SNPs
    • The International HapMap Consortium
    • The International HapMap Consortium (2007). A second generation human haplotype map of over 3.1 million SNPs. Nature, 449(7164), 851-861.
    • (2007) Nature , vol.449 , Issue.7164 , pp. 851-861
  • 69
    • 52249118137 scopus 로고    scopus 로고
    • Latent tree models and approximate inference in Bayesian networks
    • Wang, Y., Zhang, N. L., & Chen, T. (2008). Latent tree models and approximate inference in Bayesian networks. Journal of Articial Intelligence Research, 32, 879-900.
    • (2008) Journal of Articial Intelligence Research , vol.32 , pp. 879-900
    • Wang, Y.1    Zhang, N.L.2    Chen, T.3
  • 70
    • 14844351034 scopus 로고    scopus 로고
    • Not so naive Bayes: Aggregating one-dependence estimators
    • DOI 10.1007/s10994-005-4258-6
    • Webb, G. I., Boughton, J. R., & Wang, Z. (2005). Not so naive Bayes: Aggregating onedependence estimators. Machine Learning, 58(1), 5 -24. (Pubitemid 40356736)
    • (2005) Machine Learning , vol.58 , Issue.1 , pp. 5-24
    • Webb, G.I.1    Boughton, J.R.2    Wang, Z.3
  • 72
    • 2342533082 scopus 로고    scopus 로고
    • On convergence properties of the EM algorithm for gaussian mixtures
    • Xu, L., & Jordan, M. I. (1996). On convergence properties of the EM algorithm for Gaussian mixtures. Neural Computation, 8(1), 129-151. (Pubitemid 126449919)
    • (1996) Neural Computation , vol.8 , Issue.1 , pp. 129-151
    • Xu, L.1    Jordan, M.I.2
  • 73
    • 16444383160 scopus 로고    scopus 로고
    • Survey of clustering algorithms
    • DOI 10.1109/TNN.2005.845141
    • Xu, R., & Wunsch, D. (2005). Survey of clustering algorithms. IEEE Transactions on Neural Networks, 16(3), 645-678. (Pubitemid 40718010)
    • (2005) IEEE Transactions on Neural Networks , vol.16 , Issue.3 , pp. 645-678
    • Xu, R.1    Wunsch II, D.2
  • 75
    • 21844479166 scopus 로고    scopus 로고
    • Hierarchical latent class models for cluster analysis
    • Zhang, N. L. (2004). Hierarchical latent class models for cluster analysis. The Journal of Machine Learning Research, 5, 697-723.
    • (2004) The Journal of Machine Learning Research , vol.5 , pp. 697-723
    • Zhang, N.L.1
  • 76
    • 10844274360 scopus 로고    scopus 로고
    • Effective dimensions of hierarchical latent class models
    • Zhang, N. L., & Kocka, T. (2004a). Effective dimensions of hierarchical latent class models. Journal of Articial Intelligence Research, 21, 1-17. (Pubitemid 41525895)
    • (2004) Journal of Artificial Intelligence Research , vol.21 , pp. 1-17
    • Zhang, N.L.1    Kocka, T.2
  • 78
    • 1842815760 scopus 로고    scopus 로고
    • Latent variable discovery in classification models
    • DOI 10.1016/j.artmed.2003.11.004, PII S0933365703001350
    • Zhang, N. L., Nielsen, T. D., & Jensen, F. V. (2004). Latent variable discovery in classification models. Artificial Intelligence in Medicine, 30(3), 283-299. (Pubitemid 38471897)
    • (2004) Artificial Intelligence in Medicine , vol.30 , Issue.3 , pp. 283-299
    • Zhang, N.L.1    Nielsen, T.D.2    Jensen, F.V.3
  • 79
    • 44449153601 scopus 로고    scopus 로고
    • Discovery of latent structures: Experience with the CoIL Challenge 2000 data set
    • DOI 10.1007/s11424-008-9101-2
    • Zhang, N. L., Wang, Y., & Chen, T. (2008). Discovery of latent structures: Experience with the CoIL Challenge 2000 data set&z.ast;. Journal of Systems Science and Complexity, 21(2), 172-183. (Pubitemid 351768543)
    • (2008) Journal of Systems Science and Complexity , vol.21 , Issue.2 , pp. 172-183
    • Zhang, N.L.1    Wang, Y.2    Chen, T.3
  • 80
    • 39149116693 scopus 로고    scopus 로고
    • Latent tree models and diagnosis in traditional Chinese medicine
    • Zhang, N. L., Yuan, S., Chen, T., & Wang, Y. (2008). Latent tree models and diagnosis in traditional Chinese medicine. Artificial Intelligence in Medicine, 42(3), 229-245.
    • (2008) Artificial Intelligence in Medicine , vol.42 , Issue.3 , pp. 229-245
    • Zhang, N.L.1    Yuan, S.2    Chen, T.3    Wang, Y.4


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