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Volumn 20, Issue 2, 2009, Pages 165-172

Optimization and knowledge-based technologies

Author keywords

Data mining; Knowledge based technologies; Optimization; Statistical learning; Visualization

Indexed keywords


EID: 67651236892     PISSN: 08684952     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (15)

References (35)
  • 1
    • 67651212147 scopus 로고    scopus 로고
    • Stochastic optimization algorithms for support vector machines classification
    • Bartkutė-Norkūnienė, V. (2009). Stochastic optimization algorithms for support vector machines classification. Informatica, 20(2), 173-186.
    • (2009) Informatica , vol.20 , Issue.2 , pp. 173-186
    • Bartkutė-Norkūnienė, V.1
  • 2
    • 67651211132 scopus 로고    scopus 로고
    • On a minimal spanning tree approach in the cluster validation problem
    • Barzily, B., Z. Volkovich, B. Akteke-Öztürk, G.-W. Weber (2009). On a minimal spanning tree approach in the cluster validation problem. Informatica, 20(2), 187-202.
    • (2009) Informatica , vol.20 , Issue.2 , pp. 187-202
    • Barzily, B.1    Volkovich, Z.2    Akteke-Öztürk, B.3    Weber, G.-W.4
  • 3
    • 67651248548 scopus 로고    scopus 로고
    • Laplacian eigenmaps for dimensionality
    • Belkin M., Niyogi P. (2003). Laplacian eigenmaps for dimensionality. Speech Communication, 1(2-3), 349-367.
    • (2003) Speech Communication , vol.1 , Issue.2-3 , pp. 349-367
    • Belkin, M.1    Niyogi, P.2
  • 5
    • 0030376226 scopus 로고    scopus 로고
    • Measuring the influence of individual data points in a cluster analysis
    • Cheng, R., et al. (1996). Measuring the influence of individual data points in a cluster analysis, Journal Classification, 13, 315-335.
    • (1996) Journal Classification , vol.13 , pp. 315-335
    • Cheng, R.1
  • 6
    • 34249753618 scopus 로고
    • Support-vector networks
    • Cortes, C., and V. Vapnik (1995). Support-vector networks. Machine Learning, 20(3), 273-297.
    • (1995) Machine Learning , vol.20 , Issue.3 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 8
    • 0001829246 scopus 로고
    • Introduction to grey system theory
    • Deng, J.L. (1988a). Introduction to grey system theory. The Journal of Grey Theory, 1, 1-24.
    • (1988) The Journal of Grey Theory , vol.1 , pp. 1-24
    • Deng, J.L.1
  • 9
    • 0035961983 scopus 로고    scopus 로고
    • Visualization of a set of parameters characterized by their correlation matrix
    • Dzemyda, G. (2001). Visualization of a set of parameters characterized by their correlation matrix. Computational Statistics and Data Analysis, 36(10), 15-30.
    • (2001) Computational Statistics and Data Analysis , vol.36 , Issue.10 , pp. 15-30
    • Dzemyda, G.1
  • 10
    • 31344439545 scopus 로고    scopus 로고
    • Heuristic approach for minimizing the projection error in the integrated mapping
    • Dzemyda, G., O. Kurasova (2006). Heuristic approach for minimizing the projection error in the integrated mapping. European Journal of Operation Research, 171, 859-878.
    • (2006) European Journal of Operation Research , vol.171 , pp. 859-878
    • Dzemyda, G.1    Kurasova, O.2
  • 12
    • 67651232986 scopus 로고    scopus 로고
    • Continuous nonlinear programming techniques to solve scheduling problems
    • Fagundez F., A. Xavier and J.L.D. Faco (2009). Continuous nonlinear programming techniques to solve scheduling problems. Informatica, 20(2), 203-216.
    • (2009) Informatica , vol.20 , Issue.2 , pp. 203-216
    • Fagundez, F.1    Xavier, A.2    Faco, J.L.D.3
  • 13
    • 0000673504 scopus 로고
    • Multivariate generalizations of the Wolfowitz and Smirnov two-sample tests
    • Friedman, J., et al. (1979). Multivariate generalizations of the Wolfowitz and Smirnov two-sample tests, Annals of Statistics, 7, 697-717.
    • (1979) Annals of Statistics , vol.7 , pp. 697-717
    • Friedman, J.1
  • 14
    • 31244436918 scopus 로고    scopus 로고
    • Augmented Lagrangean duality and nondifferantiable optimization methods in nonconvex programming
    • Gasimov R. (2002). Augmented Lagrangean duality and nondifferantiable optimization methods in nonconvex programming. Journal of Global Optimization, 24, 187-203.
    • (2002) Journal of Global Optimization , vol.24 , pp. 187-203
    • Gasimov, R.1
  • 16
    • 37549050953 scopus 로고    scopus 로고
    • An optimization of system for automatic recognition of ischemic stroke areas in computed tomography images
    • Grigaitis, D., V. Bartkutė, L. Sakalauskas (2007). An optimization of system for automatic recognition of ischemic stroke areas in computed tomography images. Informatica, 18(4), 603-614.
    • (2007) Informatica , vol.18 , Issue.4 , pp. 603-614
    • Grigaitis, D.1    Bartkutė, V.2    Sakalauskas, L.3
  • 20
    • 34648830355 scopus 로고
    • Complexity of connectionist learning with various node functions. COINS
    • Technical Report, No. 87-60. University of Massachusetts
    • Judd, J.S. (1987). Complexity of connectionist learning with various node functions. COINS. Technical Report, No. 87-60. University of Massachusetts.
    • (1987)
    • Judd, J.S.1
  • 21
    • 67651225576 scopus 로고    scopus 로고
    • Topology preservation measures in the visualization of manifoldtype multidimensional data
    • Karbauskaitė, R., and G. Dzemyda (2009). Topology preservation measures in the visualization of manifoldtype multidimensional data. Informatica, 20(2), 235-254.
    • (2009) Informatica , vol.20 , Issue.2 , pp. 235-254
    • Karbauskaitė, R.1    Dzemyda, G.2
  • 22
    • 67651238860 scopus 로고    scopus 로고
    • On the complexity and approximability of committee polyhedral separability
    • Khachay, M., and M. Pobery (2009). On the complexity and approximability of committee polyhedral separability. Informatica, 20(2), 217-234.
    • (2009) Informatica , vol.20 , Issue.2 , pp. 217-234
    • Khachay, M.1    Pobery, M.2
  • 24
    • 0026152917 scopus 로고
    • Complexity results on learning by neural nets
    • Lin, J.H., J.S. Vitter (1991). Complexity results on learning by neural nets. Machine Learning, 6, 211-230.
    • (1991) Machine Learning , vol.6 , pp. 211-230
    • Lin, J.H.1    Vitter, J.S.2
  • 25
    • 0029270805 scopus 로고
    • Artificial neural networks for feature extraction and multivariate data projection
    • Mao, J., A.K. Jain (1995). Artificial neural networks for feature extraction and multivariate data projection. IEEE Trans. Neural Networks, 6, 296-317.
    • (1995) IEEE Trans. Neural Networks , vol.6 , pp. 296-317
    • Mao, J.1    Jain, A.K.2
  • 26
    • 0037433759 scopus 로고    scopus 로고
    • GAAS: Gene array analyzer software for management, analysis and visualization of gene expression data
    • Masseroli, M., P. Cerveri, P.G. Pelicci, M. Alcalay (2003). GAAS: gene array analyzer software for management, analysis and visualization of gene expression data. Bioinformatics, 19(6), 774-775.
    • (2003) Bioinformatics , vol.19 , Issue.6 , pp. 774-775
    • Masseroli, M.1    Cerveri, P.2    Pelicci, P.G.3    Alcalay, M.4
  • 27
    • 33746048799 scopus 로고    scopus 로고
    • Optimization of the local search in the training for SAMANN neural network
    • Medvedev, V., G. Dzemyda (2006). Optimization of the local search in the training for SAMANN neural network. Journal of Global Optimization, 35, 607-623.
    • (2006) Journal of Global Optimization , vol.35 , pp. 607-623
    • Medvedev, V.1    Dzemyda, G.2
  • 28
    • 67651222596 scopus 로고    scopus 로고
    • Testing of hybrid genetic algorithms for structured quadratic assignment problems
    • Misevičius, A. and D. Rubliauskas (2009). Testing of hybrid genetic algorithms for structured quadratic assignment problems. Informatica, 20(2), 255-272.
    • (2009) Informatica , vol.20 , Issue.2 , pp. 255-272
    • Misevičius, A.1    Rubliauskas, D.2
  • 29
    • 67651229638 scopus 로고    scopus 로고
    • On stochastic optimization and statistical learning in reproducing kernel Hilbert spaces by SVM
    • Norkin, V., and M. Keyzer (2009). On stochastic optimization and statistical learning in reproducing kernel Hilbert spaces by SVM. Informatica, 20(2), 273-292.
    • (2009) Informatica , vol.20 , Issue.2 , pp. 273-292
    • Norkin, V.1    Keyzer, M.2
  • 30
    • 33748922410 scopus 로고    scopus 로고
    • Modelling and simulation of business systems
    • Sakalauskas, L. (2006). Modelling and simulation of business systems. European Journal of Operational Research, 175(3), 1339-14330.
    • (2006) European Journal of Operational Research , vol.175 , Issue.3 , pp. 1339-14330
    • Sakalauskas, L.1
  • 31
    • 2342517502 scopus 로고    scopus 로고
    • Think globally, fit locally: Unsupervised learning of low dimensional manifolds
    • Saul, L.K, and S.T. Roweis (2003). Think globally, fit locally: unsupervised learning of low dimensional manifolds. J. Machine Learning Research, 4, 119-155.
    • (2003) J. Machine Learning Research , vol.4 , pp. 119-155
    • Saul, L.K.1    Roweis, S.T.2
  • 32
    • 67651225583 scopus 로고    scopus 로고
    • The performance of the modified subgradient algorithm on solving the 0-1 quadratic knapsack problem
    • Sipahioglu, A., and T. Sarac (2009). The performance of the modified subgradient algorithm on solving the 0-1 quadratic knapsack problem. Informatica, 20(2), 293-304.
    • (2009) Informatica , vol.20 , Issue.2 , pp. 293-304
    • Sipahioglu, A.1    Sarac, T.2
  • 33
    • 0034348378 scopus 로고    scopus 로고
    • Convergence of the simulated annealing algorithm for continuous global optimization
    • Yang (2000). Convergence of the simulated annealing algorithm for continuous global optimization. Journal of Optimization Theory and Applications, 104(3), 691-716.
    • (2000) Journal of Optimization Theory and Applications , vol.104 , Issue.3 , pp. 691-716
    • Yang1
  • 34
    • 85041756602 scopus 로고    scopus 로고
    • Goldman Sachs. New York, Vault, Inc
    • Vault (2006). Vault Employer Profile. Goldman Sachs. New York, Vault, Inc.
    • (2006) Vault Employer Profile
    • Vault1
  • 35
    • 67651225590 scopus 로고    scopus 로고
    • Multi-attribute decision-making model by applying grey numbers
    • Zavadskas, E.K., A. Kaklauskas, Z. Turskis, J. Tamošaitienė (2009). Multi-attribute decision-making model by applying grey numbers. Informatica, 20(2), 305-320.
    • (2009) Informatica , vol.20 , Issue.2 , pp. 305-320
    • Zavadskas, E.K.1    Kaklauskas, A.2    Turskis, Z.3    Tamošaitienė, J.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.