메뉴 건너뛰기




Volumn 53, Issue 10, 2010, Pages 95-103

Nonparametric belief propagation

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATE INFERENCE; BELIEF PROPAGATION; BP ALGORITHM; COMPLEX MODEL; CONTINUOUS QUANTITIES; CONTINUOUS VARIABLES; DISTRIBUTED LOCALIZATION; FILTERING TECHNIQUE; GAUSSIAN MIXTURES; MARKOV RANDOM FIELDS; NON-PARAMETRIC; NON-PARAMETRIC BELIEF PROPAGATION; PARTICLE FILTERING; PROBABILISTIC GRAPHICAL MODELS; REAL-WORLD; VISUAL MOTION;

EID: 77957966295     PISSN: 00010782     EISSN: 15577317     Source Type: Journal    
DOI: 10.1145/1831407.1831431     Document Type: Article
Times cited : (152)

References (51)
  • 1
    • 0015385037 scopus 로고
    • Nonlinear Bayesian estimationusing Gaussian sumapproximations, Morgan Kaufmann
    • Aug.
    • Alspach, D.L. and Sorenson, H.W.Nonlinear Bayesian estimationusing Gaussian sumapproximations, Morgan Kaufmann.IEEE Trans. AC 17, 4 (Aug. 1972), 439-448.
    • (1972) IEEE Trans. AC , vol.17 , Issue.4 , pp. 439-448
    • Alspach, D.L.1    Sorenson, H.W.2
  • 4
    • 72949124697 scopus 로고    scopus 로고
    • Bayesian compressive sensingvia belief propagation
    • Baron, D., Sarvotham, S., Baraniuk,R.G. Bayesian compressive sensingvia belief propagation. IEEETrans. Sig. Proc. 58, 1 (2010), 269-280.
    • (2010) IEEETrans. Sig. Proc. , vol.58 , Issue.1 , pp. 269-280
    • Baron, D.1    Sarvotham, S.2    Baraniuk, R.G.3
  • 5
    • 33847156958 scopus 로고    scopus 로고
    • Sequential auxiliary particle beliefpropagation
    • Briers, M., Doucet, A., Singh, S.S.Sequential auxiliary particle beliefpropagation. In ICIF (2005), 705-711.
    • (2005) ICIF , pp. 705-711
    • Briers, M.1    Doucet, A.2    Singh, S.S.3
  • 6
    • 44649107771 scopus 로고    scopus 로고
    • An overview of existing methods andrecent advances in sequential MonteCarlo.
    • May
    • Cappé, O., Godsill, S.J., Moulines, E.An overview of existing methods andrecent advances in sequential MonteCarlo. Proc. IEEE 95, 5 (May 2007), 899-924.
    • (2007) Proc IEEE , vol.95 , Issue.5 , pp. 899-924
    • Cappé, O.1    Godsill Moulines, J.S.E.2
  • 7
    • 34047122682 scopus 로고    scopus 로고
    • Dynamicquantization for belief propagationin sparse spaces.
    • Coughlan, J., Shen, H. Dynamicquantization for belief propagationin sparse spaces. Comput. Vis.Image Underst. 106, 1 (2007), 47-58.
    • (2007) Comput. Vis.Image Underst. , vol.106 , Issue.1 , pp. 47-58
    • Coughlan, J.1    Shen, H.2
  • 8
    • 9744280150 scopus 로고    scopus 로고
    • Findingdeformable shapes using loopy beliefpropagation
    • Coughlan, J.M., Ferreira, S.J. Findingdeformable shapes using loopy beliefpropagation. In ECCV, vol. 3, (2002), 453-468.
    • (2002) ECCV , vol.3 , pp. 453-468
    • Coughlan, J.M.1    Ferreira, S.J.2
  • 11
    • 0003665481 scopus 로고    scopus 로고
    • Doucet A.,de Freitas N,Gordon N.,eds. Springer-Verlag, New York
    • Doucet, A., de Freitas, N., Gordon, N.,eds. Sequential Monte Carlo Methodsin Practice. Springer-Verlag, New York, 2001.
    • (2001) Sequential Monte Carlo Methodsin Practice
  • 12
    • 27144476505 scopus 로고
    • Implementationof continuous Bayesian networksusing sums of weighted Gaussians
    • Driver, E., Morrell, D. Implementationof continuous Bayesian networksusing sums of weighted Gaussians.In UAI (1995), 134-140.
    • (1995) UAI , pp. 134-140
    • Driver, E.1    Morrell, D.2
  • 13
    • 4644354464 scopus 로고    scopus 로고
    • Pictorial structures for objectrecognition
    • Felzenszwalb, P.F., Huttenlocher,D.P. Pictorial structures for objectrecognition. IJCV 61, 1 (2005), 55-79.
    • (2005) IJCV , vol.61 , Issue.1 , pp. 55-79
    • Felzenszwalb, P.F.1    Huttenlocher, D.P.2
  • 15
    • 84898964205 scopus 로고    scopus 로고
    • A revolution:Belief propagation in graphs withcycles
    • MIT Press
    • Frey, B.J., MacKay, D.J.C. A revolution:Belief propagation in graphs withcycles. In NIPS 10 (1998), MIT Press, 479-485.
    • (1998) NIPS , vol.10 , pp. 479-485
    • Frey, B.J.1    MacKay, D.J.C.2
  • 16
    • 77957940079 scopus 로고    scopus 로고
    • AND/ORimportance sampling
    • Gogate, V., Dechter, R. AND/ORimportance sampling. In UAI (2008), 212-219.
    • (2008) UAI , pp. 212-219
    • Gogate, V.1    Dechter, R.2
  • 17
    • 63549108724 scopus 로고    scopus 로고
    • Learning nonparametric modelsfor probabilistic imitation
    • MIT Press
    • Grimes, D.B., Rashid, D.R., Rao, R.P.Learning nonparametric modelsfor probabilistic imitation. In NIPS(2007), MIT Press, 521-528.
    • (2007) NIPS , pp. 521-528
    • Grimes, D.B.1    Rashid, D.R.2    Rao, R.P.3
  • 18
    • 64149131309 scopus 로고    scopus 로고
    • Hotcoupling: A particle approachto inference and normalizationon pairwise undirected graphsof arbitrary topology
    • MIT Press
    • Hamze, F., de Freitas, N. Hotcoupling: A particle approachto inference and normalizationon pairwise undirected graphsof arbitrary topology. InNIPS 18 (2006), MIT Press, 491-498.
    • (2006) NIPS , vol.18 , pp. 491-498
    • Hamze, F.1    De Freitas, N.2
  • 19
    • 33845562516 scopus 로고    scopus 로고
    • Efficient nonparametric beliefpropagation with application toarticulated body tracking
    • Han, T.X., Ning, H., Huang, T.S.Efficient nonparametric beliefpropagation with application toarticulated body tracking. In CVPR(2006), 214-221.
    • (2006) CVPR , pp. 214-221
    • Han, T.X.1    Ning, H.2    Huang, T.S.3
  • 20
    • 6344281239 scopus 로고    scopus 로고
    • On the uniqueness of loopybelief propagation fixed points
    • Heskes, T. On the uniqueness of loopybelief propagation fixed points. NeuralComp. 16 (2004), 2379-2413.
    • (2004) NeuralComp. , vol.16 , pp. 2379-2413
    • Heskes, T.1
  • 21
    • 77955358601 scopus 로고    scopus 로고
    • Particlebelief propagation
    • Ihler, A., McAllester, D. Particlebelief propagation. In AI Stat. 12(2009).
    • (2009) AI Stat. , vol.12
    • Ihler, A.1    McAllester, D.2
  • 22
    • 17144417306 scopus 로고    scopus 로고
    • Nonparametric beliefpropagation for self-localizationof sensor networks
    • Apr.
    • Ihler, A.T., Fisher, J.W., Moses, R.L.,Willsky, A.S. Nonparametric beliefpropagation for self-localizationof sensor networks. IEEE J. Sel.Areas Commun. 23, 4 (Apr. 2005), 809-819.
    • (2005) IEEE J. Sel.Areas Commun. , vol.23 , Issue.4 , pp. 809-819
    • Ihler, A.T.1    Fisher, J.W.2    Moses, R.L.3    Willsky, A.S.4
  • 23
    • 21844467514 scopus 로고    scopus 로고
    • Loopy belief propagation: Convergenceand effects of message errors
    • Ihler, A.T., Fisher, J.W., Willsky, A.S.Loopy belief propagation: Convergenceand effects of message errors. JMLR6 (2005), 905-936.
    • (2005) JMLR , vol.6 , pp. 905-936
    • Ihler, A.T.1    Fisher, J.W.2    Willsky, A.S.3
  • 24
    • 77957961174 scopus 로고    scopus 로고
    • Particle-based variational inference for continuous systems
    • Ihler, A.T., Frank, A.J., Smyth, P.Particle-based variational inference for continuous systems. In NIPS 22(2009), 826-834.
    • (2009) NIPS , vol.22 , pp. 826-834
    • Ihler, A.T.1    Frank, A.J.2    Smyth, P.3
  • 25
    • 84898929223 scopus 로고    scopus 로고
    • Efficient multiscalesampling from products of Gaussianmixtures
    • MITPress
    • Ihler, A.T., Sudderth, E.B., Freeman,W.T., Willsky, A.S. Efficient multiscalesampling from products of Gaussianmixtures. In NIPS 16 (2004), MITPress.
    • (2004) NIPS , vol.16
    • Ihler, A.T.1    Sudderth, E.B.2    Freeman, W.T.3    Willsky, A.S.4
  • 26
    • 17544404795 scopus 로고    scopus 로고
    • PAMPAS:Real-valuedgraphical models for computervision
    • Isard, M. PAMPAS : Real-valuedgraphical models for computervision. In CVPR, vol. 1 (2003), 613-620.
    • (2003) CVPR , vol.1 , pp. 613-620
    • Isard, M.1
  • 27
    • 84858779894 scopus 로고    scopus 로고
    • Continuously-adaptive discretizationfor message-passing algorithms
    • MIT Press
    • Isard, M., MacCormick, J., Achan, K.Continuously-adaptive discretizationfor message-passing algorithms.In NIPS (2009), MIT Press, 737-744.
    • (2009) NIPS , pp. 737-744
    • Isard, M.1    MacCormick, J.2    Achan, K.3
  • 28
    • 4043129651 scopus 로고    scopus 로고
    • Graphical models
    • Jordan, M.I. Graphical models. Stat.Sci. 19, 1 (2004), 140-155.
    • (2004) Stat.Sci. , vol.19 , Issue.1 , pp. 140-155
    • Jordan, M.I.1
  • 29
    • 0041918994 scopus 로고    scopus 로고
    • General algorithm for approximate inference and its application tohybrid Bayes nets
    • Morgan Kaufmann
    • Koller, D., Lerner, U., Angelov, D.A general algorithm for approximate inference and its application tohybrid Bayes nets. In UAI 15(1999), Morgan Kaufmann, 324-333.
    • (1999) UAI , vol.15 , pp. 324-333
    • Koller, D.1    Lerner, U.2    Angelov, D.A.3
  • 30
    • 0035246564 scopus 로고    scopus 로고
    • Factor graphs and the sumproductalgorithm
    • Feb.
    • Kschischang, F.R., Frey, B.J., Loeliger,H.-A. Factor graphs and the sumproductalgorithm. IEEE Trans. IT 47,2 (Feb. 2001), 498-519.
    • (2001) IEEE Trans. IT , vol.47 , Issue.2 , pp. 498-519
    • Kschischang, F.R.1    Frey, B.J.2    Loeligerh, A.3
  • 31
    • 52349102984 scopus 로고    scopus 로고
    • Messagepassingdecoding of lattices usingGaussian mixtures
    • July
    • Kurkoski, B., Dauwels, J. Messagepassingdecoding of lattices usingGaussian mixtures. In ISIT (July2008).
    • (2008) ISIT
    • Kurkoski, B.1    Dauwels, J.2
  • 32
    • 0042565834 scopus 로고    scopus 로고
    • HierarchicalBayesian inference in the visualcortex.
    • July
    • Lee, T.S., Mumford, D. HierarchicalBayesian inference in the visualcortex. J. Opt. Soc. Am. A 20, 7(July 2003), 1434-1448.
    • (2003) J. Opt. Soc. Am. , vol.20 , Issue.7 , pp. 1434-1448
    • Lee, T.S.1    Mumford, D.2
  • 33
    • 33749990780 scopus 로고    scopus 로고
    • Survey of advances in vision-basedhuman motion capture and analysis. Comput
    • Moeslund, T.B., Hilton, A., Kruger, V.A survey of advances in vision-basedhuman motion capture and analysis.Comput. Vision Image Underst. 104(2006), 90-126.
    • (2006) Vision Image Underst. , vol.104 , pp. 90-126
    • Moeslund, T.B.1    Hilton, A.2    Kruger, V.A.3
  • 34
    • 57149125289 scopus 로고    scopus 로고
    • Sufficientconditions for convergence ofthe sum-product algorithm
    • Dec.
    • Mooij, J.M., Kappen, H.J. Sufficientconditions for convergence ofthe sum-product algorithm.IEEE Trans. IT 53, 12 (Dec. 2007), 4422-4437.
    • (2007) IEEE Trans. IT , vol.53 , Issue.12 , pp. 4422-4437
    • Mooij, J.M.1    Kappen, H.J.2
  • 35
    • 84898932109 scopus 로고    scopus 로고
    • Inferring state sequences fornon-linear systems withembedded hidden Markovmodels
    • MIT Press
    • Neal, R.M., Beal, M.J., Roweis, S.T. Inferring state sequences fornon-linear systems withembedded hidden Markovmodels. In NIPS 16 (2004),MIT Press.
    • (2004) NIPS , vol.16
    • Neal, R.M.1    Beal, M.J.2    Roweis, S.T.3
  • 36
    • 34547914903 scopus 로고    scopus 로고
    • Inference in hybrid Bayesiannetworks using dynamicdiscretization
    • Neil, M., Tailor, M., Marquez, D. Inference in hybrid Bayesiannetworks using dynamicdiscretization. Stat. Comput. 17, 3(2007), 219-233.
    • (2007) Stat. Comput. , vol.17 , Issue.3 , pp. 219-233
    • Neil, M.1    Tailor, M.2    Marquez, D.3
  • 39
    • 34547501642 scopus 로고    scopus 로고
    • Multi-scaleMCMC methods for sampling fromproducts of Gaussian mixtures
    • III-1201-III-1204
    • Rudoy, D. Wolf, P.J. Multi-scaleMCMC methods for sampling fromproducts of Gaussian mixtures.In ICASSP, vol. 3 (2007), III-1201-III-1204.
    • (2007) ICASSP , vol.3
    • Rudoy, D.1    Wolf, P.J.2
  • 40
    • 77957938896 scopus 로고    scopus 로고
    • Gaussian processbelief propagation
    • Seeger M. Gaussian processbelief propagation. InPredicting structured data(2007), 301-318.
    • (2007) Predicting Structured Data , pp. 301-318
    • Seeger, M.1
  • 46
    • 54949089986 scopus 로고    scopus 로고
    • Learning thedynamics and time-recursiveboundary detection of deformableobjects
    • Nov.
    • Sun, W., Cetin, M., Chan, R., Willsky, A.S. Learning thedynamics and time-recursiveboundary detection of deformableobjects. IEEE Trans. IP 17, 11(Nov. 2008), 2186-2200.
    • (2008) IEEE Trans. IP , vol.17 , Issue.11 , pp. 2186-2200
    • Sun, W.1    Cetin, M.2    Chan, R.3    Willsky, A.S.4
  • 47
    • 65749118363 scopus 로고    scopus 로고
    • Graphical models, exponentialfamilies, and variational inference
    • Wainwright, M.J., Jordan, M.I.Graphical models, exponentialfamilies, and variational inference.Foundations Trends Mach. Learn. 1,(2008), 1-305.
    • (2008) Foundations Trends Mach Learn. , vol.1 , pp. 1-305
    • Wainwright, M.J.1    Jordan, M.I.2
  • 48
    • 0035335643 scopus 로고    scopus 로고
    • Hand modeling, analysis, and recognition
    • May
    • Wu, Y., Huang, T.S. Hand modeling,analysis, and recognition. IEEESignal Proc. Mag. (May 2001), 51-60.
    • (2001) IEEESignal Proc. Mag , pp. 51-60
    • Wu, Y.1    Huang, T.S.2
  • 49
    • 84898991014 scopus 로고    scopus 로고
    • Approximate inference and protein-folding
    • MIT Press
    • Yanover, C., Weiss, Y. Approximate inference and protein-folding.In NIPS 16 (2003), MIT Press, 1457-1464.
    • (2003) NIPS , vol.16 , pp. 1457-1464
    • Yanover, C.1    Weiss, Y.2
  • 51
    • 23744513375 scopus 로고    scopus 로고
    • Constructing free energyapproximations and generalizedbelief propagation algorithms
    • July
    • Yedidia, J.S., Freeman, W.T.,Weiss, Y. Constructing free energyapproximations and generalizedbelief propagation algorithms. IEEE Trans. IT 51, 7 (July 2005), 2282-2312.
    • (2005) IEEE Trans. IT , vol.51 , Issue.7 , pp. 2282-2312
    • Yedidia, J.S.1    Freeman, W.T.2    Weiss, Y.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.