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Volumn , Issue , 2012, Pages 1065-1070

How to infer the informational energy from small datasets

Author keywords

[No Author keywords available]

Indexed keywords

FIXED POSITIVE INTEGERS; NEAREST NEIGHBOR DISTANCE; NON-PARAMETRIC; SAMPLE POINT; SMALL DATA SET; STANDARD DISTRIBUTIONS;

EID: 84864667521     PISSN: 18420133     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/OPTIM.2012.6231921     Document Type: Conference Paper
Times cited : (8)

References (35)
  • 3
    • 0022895406 scopus 로고
    • Sets with small generalized kolmogorov complexity
    • J. L. Balcázar and R. V. Book, "Sets with small generalized Kolmogorov complexity," Acta Inf., vol. 23, no. 6, pp. 679-688, 1986.
    • (1986) Acta Inf. , vol.23 , Issue.6 , pp. 679-688
    • Balcázar, J.L.1    Book, R.V.2
  • 6
    • 0032022729 scopus 로고    scopus 로고
    • Neural-network design for small training sets of high dimension
    • J.-L. Yuan and T. Fine, "Neural-network design for small training sets of high dimension," IEEE Tnansactions on Neural Networks, vol. 9, pp. 266-280, 1998.
    • (1998) IEEE Tnansactions on Neural Networks , vol.9 , pp. 266-280
    • Yuan, J.-L.1    Fine, T.2
  • 8
  • 10
    • 33748743279 scopus 로고    scopus 로고
    • Using mega-trend-diffusion and artificial samples in small data set learning for early flexible manufacturing system scheduling knowledge
    • D.-C. Li, C.-S. Wu, T. T.-I., and L. Y.-S., "Using mega-trend-diffusion and artificial samples in small data set learning for early flexible manufacturing system scheduling knowledge," Computers and Operations Research, vol. 34, pp. 966-982, 2007.
    • (2007) Computers and Operations Research , vol.34 , pp. 966-982
    • Li, D.-C.1    Wu, C.-S.2    T, T.-I.3    L, Y.-S.4
  • 12
    • 27344432371 scopus 로고    scopus 로고
    • Using mega-fuzzification and data trend estimation in small data set learning for early FMS scheduling knowledge
    • D.-C. Li, C.-S. Wu, T.-I. Tsai, and F. M. Chang, "Using mega-fuzzification and data trend estimation in small data set learning for early FMS scheduling knowledge," Comput. Oper. Res., vol. 33, no. 6, pp. 1857-1869, 2006.
    • (2006) Comput. Oper. Res. , vol.33 , Issue.6 , pp. 1857-1869
    • Li, D.-C.1    Wu, C.-S.2    Tsai, T.-I.3    Chang, F.M.4
  • 13
    • 34248545085 scopus 로고    scopus 로고
    • Approximate modeling for high order nonlinear functions using small sample sets
    • T.-I. Tsai and D.-C. Li, "Approximate modeling for high order nonlinear functions using small sample sets," Expert Syst. Appl., vol. 34, no. 1, pp. 564-569, 2008.
    • (2008) Expert Syst. Appl. , vol.34 , Issue.1 , pp. 564-569
    • Tsai, T.-I.1    Li, D.-C.2
  • 14
    • 34248571379 scopus 로고    scopus 로고
    • A non-parametric learning algorithm for small manufacturing data sets
    • D.-C. Li and C.-W. Yeh, "A non-parametric learning algorithm for small manufacturing data sets," Expert Syst. Appl., vol. 34, no. 1, pp. 391-398, 2008.
    • (2008) Expert Syst. Appl. , vol.34 , Issue.1 , pp. 391-398
    • Li, D.-C.1    Yeh, C.-W.2
  • 15
    • 64049110475 scopus 로고    scopus 로고
    • A neural network weight determination model designed uniquely for small data set learning
    • D.-C. Li and C.-W. Liu, "A neural network weight determination model designed uniquely for small data set learning," Expert Syst. Appl., vol. 36, no. 6, pp. 9853-9858, 2009.
    • (2009) Expert Syst. Appl. , vol.36 , Issue.6 , pp. 9853-9858
    • Li, D.-C.1    Liu, C.-W.2
  • 17
    • 55249120706 scopus 로고    scopus 로고
    • Selecting the most representative sample is NP-hard: Need for expert (fuzzy) knowledge
    • FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on, June
    • J. Gamez, F. Modave, and O. Kosheleva, "Selecting the most representative sample is NP-hard: Need for expert (fuzzy) knowledge," in Fuzzy Systems, 2008. FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on, June 2008, pp. 1069-1074.
    • (2008) Fuzzy Systems, 2008 , pp. 1069-1074
    • Gamez, J.1    Modave, F.2    Kosheleva, O.3
  • 18
    • 0003443397 scopus 로고
    • (Chapman & Hall/CRC Monographs on Statistics & Applied Probability). Chapman and Hall/CRC
    • B. Silverman, Density Estimation for Statistics and Data Analysis (Chapman & Hall/CRC Monographs on Statistics & Applied Probability). Chapman and Hall/CRC, 1986.
    • (1986) Density Estimation for Statistics and Data Analysis
    • Silverman, B.1
  • 19
    • 0041877169 scopus 로고    scopus 로고
    • Estimation of entropy and mutual information
    • June
    • L. Paninski, "Estimation of entropy and mutual information," Neural Comput., vol. 15, pp. 1191-1253, June 2003.
    • (2003) Neural Comput. , vol.15 , pp. 1191-1253
    • Paninski, L.1
  • 22
  • 24
    • 10944226453 scopus 로고    scopus 로고
    • An informational energy LVQ approach for feature ranking
    • pages In d-side publications
    • R. Andonie and A. Caţaron, "An informational energy LVQ approach for feature ranking," in European Symposium on Artificial Neural Networks 2004, pages In d-side publications, 2004, pp. 471-476.
    • (2004) European Symposium on Artificial Neural Networks 2004 , pp. 471-476
    • Andonie, R.1    Caţaron, A.2
  • 25
    • 10944263188 scopus 로고    scopus 로고
    • Energy generalized lvq with relevance factors
    • Proceedings. 2004 IEEE International Joint Conference on july 2
    • A. Caţaron and R. Andonie, "Energy generalized lvq with relevance factors," in Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on, vol. 2, july 2004, pp. 1421-1426 vol.2.
    • (2004) Neural Networks, 2004 , vol.2 , pp. 1421-1426
    • Caţaron, A.1    Andonie, R.2
  • 27
    • 84864672591 scopus 로고    scopus 로고
    • How to learn from small training sets
    • Manno-Lugano, Switzerland, invited talk, September
    • R. Andonie, "How to learn from small training sets," Dalle Molle Institute for Artificial Intelligence (IDSIA), Manno-Lugano, Switzerland, invited talk, September 2009.
    • (2009) Dalle Molle Institute for Artificial Intelligence (IDSIA)
    • Andonie, R.1
  • 28
    • 77955286812 scopus 로고    scopus 로고
    • Energy supervised relevance neural gas for feature ranking
    • A. Caţaron and R. Andonie, "Energy supervised relevance neural gas for feature ranking," Neural Processing Letters, vol. 32, no. 1, pp. 59-73, 2010.
    • (2010) Neural Processing Letters , vol.32 , Issue.1 , pp. 59-73
    • Caţaron, A.1    Andonie, R.2
  • 30
    • 0041371907 scopus 로고
    • Theorie de l'information. energie informationelle
    • O. Onicescu, "Theorie de l'information. energie informationelle, " C. R. Acad. Sci. Paris, Ser. A-B, no. 263, pp. 841-842, 1966.
    • (1966) C. R. Acad. Sci. Paris, ser. A-B , Issue.263 , pp. 841-842
    • Onicescu, O.1
  • 32
    • 0023325560 scopus 로고
    • Sample estimate of the entropy of a random vector
    • L. F. Kozachenko and N. N. Leonenko, "Sample estimate of the entropy of a random vector," Probl. Peredachi Inf., vol. 23, no. 2, pp. 9-16, 1987.
    • (1987) Probl. Peredachi Inf. , vol.23 , Issue.2 , pp. 9-16
    • Kozachenko, L.F.1    Leonenko, N.N.2
  • 35
    • 85095141758 scopus 로고    scopus 로고
    • Ica based on a smooth estimation of the differential entropy
    • L. Faivishevsky and J. Goldberger, "Ica based on a smooth estimation of the differential entropy," in NIPS, 2008.
    • (2008) NIPS
    • Faivishevsky, L.1    Goldberger, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.