메뉴 건너뛰기




Volumn 15, Issue 4, 2004, Pages 828-837

Gradient-based manipulation of nonparametric entropy estimates

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE SYSTEMS; INFORMATION THEORY; MAXIMUM LIKELIHOOD ESTIMATION; OPTIMIZATION; PROBABILITY DENSITY FUNCTION;

EID: 3843094964     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2004.828766     Document Type: Article
Times cited : (36)

References (43)
  • 1
    • 0000335879 scopus 로고    scopus 로고
    • Parameter adaptation in stochastic optimization
    • D. Saad, Ed. Cambridge, U.K.: Cambridge Univ. Press ch. 6
    • L. B. Almeida, T. Langlois, J. D. Amaral, and A. Plakhov, "Parameter adaptation in stochastic optimization," in On-Line Learning in Neural Networks, D. Saad, Ed. Cambridge, U.K.: Cambridge Univ. Press, 1999, ch. 6, pp. 111-134.
    • (1999) On-Line Learning in Neural Networks , pp. 111-134
    • Almeida, L.B.1    Langlois, T.2    Amaral, J.D.3    Plakhov, A.4
  • 2
    • 34548281969 scopus 로고
    • Could information theory provide an ecological theory of sensory processing?
    • J. J. Atick, "Could information theory provide an ecological theory of sensory processing?," Network, vol. 3, pp. 213-251, 1992.
    • (1992) Network , vol.3 , pp. 213-251
    • Atick, J.J.1
  • 3
    • 0002014402 scopus 로고
    • Possible principles underlying the transformation of sensory messages
    • W. A. Rosenbluth, Ed. Cambridge, MA: MIT Press
    • H. B. Barlow, "Possible principles underlying the transformation of sensory messages," in Sensory Communication, W. A. Rosenbluth, Ed. Cambridge, MA: MIT Press, 1961.
    • (1961) Sensory Communication
    • Barlow, H.B.1
  • 4
    • 0001471775 scopus 로고
    • Unsupervised learning
    • H. B. Barlow, "Unsupervised learning," Neural Computat., vol. 1, no. 3, pp. 295-311, 1989.
    • (1989) Neural Computat. , vol.1 , Issue.3 , pp. 295-311
    • Barlow, H.B.1
  • 5
    • 0026586030 scopus 로고
    • A self-organizing neural network that discovers surfaces in random-dot stereograms
    • S. Becker and G. E. Hinton, "A self-organizing neural network that discovers surfaces in random-dot stereograms," Nature, vol. 355, pp. 161-163, 1992.
    • (1992) Nature , vol.355 , pp. 161-163
    • Becker, S.1    Hinton, G.E.2
  • 7
    • 0029411030 scopus 로고
    • An information-maximization approach to blind separation and blind deconvolution
    • A. J. Bell and T. J. Sejnowski, "An information-maximization approach to blind separation and blind deconvolution," Neural Computat., vol. 7, no. 6, pp. 1129-1159, 1995.
    • (1995) Neural Computat. , vol.7 , Issue.6 , pp. 1129-1159
    • Bell, A.J.1    Sejnowski, T.J.2
  • 9
    • 0001699291 scopus 로고
    • Training stochastic model recognition algorithms as networks can lead to maximum mutual information estimation of parameters
    • D. S. Touretzky, Ed. San Mateo, CA: Morgan Kaufmann
    • J. S. Bridle, "Training stochastic model recognition algorithms as networks can lead to maximum mutual information estimation of parameters," in Advances in Neural Information Processing Systems, D. S. Touretzky, Ed. San Mateo, CA: Morgan Kaufmann, 1990, vol. 2, pp. 211-217.
    • (1990) Advances in Neural Information Processing Systems , vol.2 , pp. 211-217
    • Bridle, J.S.1
  • 10
    • 0028416938 scopus 로고
    • Independent component analysis, a new concept?
    • P. Comon, "Independent component analysis, a new concept?," Signal Process., vol. 36, no. 3, pp. 287-314, 1994.
    • (1994) Signal Process. , vol.36 , Issue.3 , pp. 287-314
    • Comon, P.1
  • 11
    • 0002629270 scopus 로고
    • Maximum likelihood from incomplete data via the EM algorithm (with discussion)
    • Ser. B
    • A. P. Dempster, N. M. Laird, and D. B. Rubin, "Maximum likelihood from incomplete data via the EM algorithm (with discussion)," J. Roy. Statist. Soc. Ser. B, vol. 39, pp. 1-38, 1977.
    • (1977) J. Roy. Statist. Soc. , vol.39 , pp. 1-38
    • Dempster, A.P.1    Laird, N.M.2    Rubin, D.B.3
  • 13
    • 0041663375 scopus 로고    scopus 로고
    • Online entropy manipulation: Stochastic information gradient
    • Aug
    • D. Erdogmus, K. E. Hild II, and J. C. Principe, "Online entropy manipulation: stochastic information gradient," IEEE Signal Processing Lett., vol. 10, pp. 242-245, Aug. 2003.
    • (2003) IEEE Signal Processing Lett. , vol.10 , pp. 242-245
    • Erdogmus, D.1    Hild II, K.E.2    Principe, J.C.3
  • 14
    • 0036737108 scopus 로고    scopus 로고
    • Generalized information potential criterion for adaptive system training
    • Sept
    • D. Erdogmus and J. C. Principe, "Generalized information potential criterion for adaptive system training," IEEE Trans. Neural Networks, vol. 13, pp. 1035-1044, Sept. 2002.
    • (2002) IEEE Trans. Neural Networks , vol.13 , pp. 1035-1044
    • Erdogmus, D.1    Principe, J.C.2
  • 15
    • 0016102310 scopus 로고
    • A projection pursuit algorithm for exploratory data analysis
    • J. H. Friedman and J. W. Tukey, "A projection pursuit algorithm for exploratory data analysis," IEEE Trans. Comput., vol. 23, pp. 881-889, 1974.
    • (1974) IEEE Trans. Comput. , vol.23 , pp. 881-889
    • Friedman, J.H.1    Tukey, J.W.2
  • 16
    • 0000263797 scopus 로고
    • Projection pursuit
    • P. J. Huber, "Projection pursuit," Ann. Statist., vol. 13, no. 2, pp. 435-475, 1985.
    • (1985) Ann. Statist. , vol.13 , Issue.2 , pp. 435-475
    • Huber, P.J.1
  • 19
    • 0346494464 scopus 로고
    • Additive versus exponentiated gradient updates for linear prediction
    • New York, May
    • J. Kivinen and M. K. Warmuth, "Additive versus exponentiated gradient updates for linear prediction," in Proc. 27th Annu. ACM Symp. Theory Computing, New York, May 1995, pp. 209-218.
    • (1995) Proc. 27th Annu. ACM Symp. Theory Computing , pp. 209-218
    • Kivinen, J.1    Warmuth, M.K.2
  • 20
    • 0023981750 scopus 로고
    • Self-organization in a perceptual network
    • March
    • R. Linsker, "Self-organization in a perceptual network," Computer, pp. 105-117, March 1988.
    • (1988) Computer , pp. 105-117
    • Linsker, R.1
  • 21
    • 0034131785 scopus 로고    scopus 로고
    • On-line EM algorithm for the normalized Gaussian network
    • M.Masa-aki Sato and S. Ishii, "On-line EM algorithm for the normalized Gaussian network," Neural Computat., vol. 12, no. 2, pp. 407-432, 2000.
    • (2000) Neural Computat. , vol.12 , Issue.2 , pp. 407-432
    • Masa-aki Sato, S.1    Ishii, S.2
  • 22
    • 85106600538 scopus 로고    scopus 로고
    • Symplectic nonlinear component analysis
    • Cambridge, MA: MIT Press
    • L. C. Parra, "Symplectic nonlinear component analysis," in Advances in Neural Information Processing Systems. Cambridge, MA: MIT Press, 1996, pp. 437-443.
    • (1996) Advances in Neural Information Processing Systems , pp. 437-443
    • Parra, L.C.1
  • 23
    • 0001473437 scopus 로고
    • On the estimation of a probability density function and mode
    • E. Parzen, "On the estimation of a probability density function and mode," Ann. Math. Statist., vol. 33, pp. 1065-1076, 1962.
    • (1962) Ann. Math. Statist. , vol.33 , pp. 1065-1076
    • Parzen, E.1
  • 25
    • 0002408684 scopus 로고
    • On measures of entropy and information
    • Berkeley, CA, 1961, Reprinted in Selected Papers of Alfred Renyi Akademia Kiado, Budapest
    • A. Renyi, "On measures of entropy and information," in Proc. 4th Berkeley Symp. Mathematical Statistics and Probability, Berkeley, CA, 1961, Reprinted in Selected Papers of Alfred Renyi Akademia Kiado, Budapest, 1961, pp. 547-561.
    • (1961) Proc. 4th Berkeley Symp. Mathematical Statistics and Probability , pp. 547-561
    • Renyi, A.1
  • 27
    • 0040422903 scopus 로고
    • Learning factorial codes by predictability minimization
    • J. Schmidhuber, "Learning factorial codes by predictability minimization," Neural Computat., vol. 4, no. 6, pp. 863-879, 1992.
    • (1992) Neural Computat. , vol.4 , Issue.6 , pp. 863-879
    • Schmidhuber, J.1
  • 28
    • 0039238512 scopus 로고    scopus 로고
    • Semilinear predictability minimization produces well-known feature detectors
    • J. Schmidhuber, M. Eldracher, and B. Foltin, "Semilinear predictability minimization produces well-known feature detectors," Neural Computat., vol. 8, no. 4, pp. 773-786, 1996.
    • (1996) Neural Computat. , vol.8 , Issue.4 , pp. 773-786
    • Schmidhuber, J.1    Eldracher, M.2    Foltin, B.3
  • 30
    • 0033338205 scopus 로고    scopus 로고
    • Local gain adaptation in stochastic gradient descent
    • Edinburgh, Scotland
    • N. N. Schraudolph, "Local gain adaptation in stochastic gradient descent," in Proc. Int. Conf. Artificial Neural Networks, Edinburgh, Scotland, 1999, pp. 569-574.
    • (1999) Proc. Int. Conf. Artificial Neural Networks , pp. 569-574
    • Schraudolph, N.N.1
  • 31
    • 0036631778 scopus 로고    scopus 로고
    • Fast curvature matrix-vector products for second-order gradient descent
    • N. N. Schraudolph, "Fast curvature matrix-vector products for second-order gradient descent," Neural Computat., vol. 14, no. 7, pp. 1723-1738, 2002.
    • (2002) Neural Computat. , vol.14 , Issue.7 , pp. 1723-1738
    • Schraudolph, N.N.1
  • 33
    • 0041016997 scopus 로고
    • Unsupervised discrimination of clustered data via optimization of binary information gain
    • S. J. Hanson, J. D. Cowan, and C. L. Giles, Eds. San Mateo, CA: Morgan Kaufmann
    • N. N. Schraudolph and T. J. Sejnowski, "Unsupervised discrimination of clustered data via optimization of binary information gain," in Advances in Neural Information Processing Systems, S. J. Hanson, J. D. Cowan, and C. L. Giles, Eds. San Mateo, CA: Morgan Kaufmann, 1993, vol. 5, pp. 499-506.
    • (1993) Advances in Neural Information Processing Systems , vol.5 , pp. 499-506
    • Schraudolph, N.N.1    Sejnowski, T.J.2
  • 34
    • 0002824981 scopus 로고
    • Speeding up back-propagation
    • R. Eckmiller, Ed. Amsterdam: Elsevier
    • F. M. Silva and L. B. Almeida, "Speeding up back-propagation," in Advanced Neural Computers, R. Eckmiller, Ed. Amsterdam: Elsevier, 1990, pp. 151-158.
    • (1990) Advanced Neural Computers , pp. 151-158
    • Silva, F.M.1    Almeida, L.B.2
  • 35
    • 0001526001 scopus 로고
    • A quasi-Bayes sequential procedure for mixtures
    • A. F. M. Smith and U. E. Makov, "A quasi-Bayes sequential procedure for mixtures," J. Roy. Statist. Soc. B, vol. 40, no. 1, pp. 106-112, 1978.
    • (1978) J. Roy. Statist. Soc. B , vol.40 , Issue.1 , pp. 106-112
    • Smith, A.F.M.1    Makov, U.E.2
  • 36
    • 0025593679 scopus 로고
    • SuperSAB: Fast adaptive back propagation with good scaling properties
    • T. Tollenaere, "SuperSAB: fast adaptive back propagation with good scaling properties," Neural Networks, vol. 3, pp. 561-573, 1990.
    • (1990) Neural Networks , vol.3 , pp. 561-573
    • Tollenaere, T.1
  • 37
    • 1942450610 scopus 로고    scopus 로고
    • Feature extraction by nonparametric mutual information maximization
    • K. Torkkola, "Feature extraction by nonparametric mutual information maximization," J. Machine Learning Research, vol. 3, pp. 1415-1438, 2003.
    • (2003) J. Machine Learning Research , vol.3 , pp. 1415-1438
    • Torkkola, K.1
  • 39
    • 0005671334 scopus 로고    scopus 로고
    • The formation of topographic maps that maximize the average mutual information of the output responses to noiseless input signals
    • M. M. van Hulle, "The formation of topographic maps that maximize the average mutual information of the output responses to noiseless input signals," Neural Computat., vol. 9, no. 3, pp. 595-606, 1997.
    • (1997) Neural Computat. , vol.9 , Issue.3 , pp. 595-606
    • van Hulle, M.M.1
  • 40
    • 0001405580 scopus 로고    scopus 로고
    • Kernel-based equiprobabilistic topographic map formation
    • M. M. van Hulle, "Kernel-based equiprobabilistic topographic map formation," Neural Computat., vol. 10, no. 7, pp. 1847-1871, 1998.
    • (1998) Neural Computat. , vol.10 , Issue.7 , pp. 1847-1871
    • van Hulle, M.M.1
  • 43
    • 0029234207 scopus 로고
    • Alignment by maximization of mutual information
    • Cambridge, MA
    • P. A. Viola and W. M. Wells III, "Alignment by maximization of mutual information," in Fifth Int. Conf. Computer Vision, Cambridge, MA, 1995, pp. 16-23.
    • (1995) Fifth Int. Conf. Computer Vision , pp. 16-23
    • Viola, P.A.1    Wells III, W.M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.