Large-Scale Data Analysis Using Heuristic Methods
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[1] Karel Skokan. Technological and Economic Development of Economy , 2011 .
[2] Vítezslav Veselý,et al. Change Point Detection by Sparse Parameter Estimation , 2011, Informatica.
[3] Y. Guermeur. Sample Complexity of Classifiers Taking Values in ℝ Q , Application to Multi-Class SVMs , 2010 .
[4] Lawrence K. Saul,et al. Think Globally, Fit Locally: Unsupervised Learning of Low Dimensional Manifold , 2003, J. Mach. Learn. Res..
[5] Adilson Elias Xavier,et al. The hyperbolic smoothing clustering method , 2010, Pattern Recognit..
[6] Vaida Bartkute-Norkuniene,et al. Stochastic Optimization Algorithms for Support Vector Machines Classification , 2009, Informatica.
[7] Alessandra Durio,et al. The Minimum Density Power Divergence Approach in Building Robust Regression Models , 2011, Informatica.
[8] Gintautas Dzemyda,et al. Conditions for Optimal Efficiency of Relative MDS , 2007, Informatica.
[9] Joshua B. Tenenbaum,et al. Global Versus Local Methods in Nonlinear Dimensionality Reduction , 2002, NIPS.
[10] Kestutis Kubilius,et al. On Comparison of the Estimators of the Hurst Index of the Solutions of Stochastic Differential Equations Driven by the Fractional Brownian Motion , 2011, Informatica.
[11] G. Box. Robustness in the Strategy of Scientific Model Building. , 1979 .
[12] E. Mathieu,et al. Parametric and Non Homogeneous Semi-Markov Process for HIV Control , 2007 .
[13] Gintautas Dzemyda,et al. Dependence of locally linear embedding on the regularization parameter , 2010 .
[14] Michael C. Hout,et al. Multidimensional Scaling , 2003, Encyclopedic Dictionary of Archaeology.
[15] P. Groenen,et al. Modern multidimensional scaling , 1996 .
[16] Peter H. Millard,et al. Phase-Type Survival Trees and Mixed Distribution Survival Trees for Clustering Patients' Hospital Length of Stay , 2011, Informatica.
[17] Gintautas Dzemyda,et al. Heuristic approach for minimizing the projection error in the integrated mapping , 2006, Eur. J. Oper. Res..
[18] Judea Pearl,et al. Heuristics : intelligent search strategies for computer problem solving , 1984 .
[19] Edmundas Kazimieras Zavadskas,et al. Editorial: Optimization and intelligent decisions , 2009 .
[20] Olga Kurasova,et al. Quality of Quantization and Visualization of Vectors Obtained by Neural Gas and Self-Organizing Map , 2011, Informatica.
[21] Egidijus Rytas Vaidogas,et al. Protecting built property against fire disasters: Multi ‐attribute decision making with respect to fire risk , 2010 .
[22] Mikhail Belkin,et al. Laplacian Eigenmaps for Dimensionality Reduction and Data Representation , 2003, Neural Computation.
[23] Edmundas Kazimieras Zavadskas,et al. Integrated knowledge management model and system for construction projects , 2010, Eng. Appl. Artif. Intell..
[24] Kwan-Liu Ma,et al. An Interface Design for Future Cloud-Based Visualization Services , 2010, 2010 IEEE Second International Conference on Cloud Computing Technology and Science.
[25] Gintautas Dzemyda,et al. Web Application for Large-Scale Multidimensional Data Visualization , 2011 .
[26] Stochastic Optimization Algorithms for Support Vector Machines Classification , 2009 .
[27] Edmundas Kazimieras Zavadskas,et al. Multicriteria evaluation of apartment blocks maintenance contractors: Lithuanian case study , 2009 .
[28] Ian T. Jolliffe,et al. Principal Component Analysis , 2002, International Encyclopedia of Statistical Science.
[29] Dr. Zbigniew Michalewicz,et al. How to Solve It: Modern Heuristics , 2004 .
[30] Yoonsuck Choe,et al. Fast and accurate retinal vasculature tracing and kernel-Isomap-based feature selection , 2009, 2009 International Joint Conference on Neural Networks.
[31] Leonidas Sakalauskas,et al. Heuristic and stochastic methods in optimization , 2006, Eur. J. Oper. Res..
[32] Rimantas Rudzkis,et al. Statistical Classification of Scientific Publications , 2010, Informatica.
[33] Fernando Y. Chiyoshi,et al. A statistical analysis of simulated annealing applied to the p-median problem , 2000, Ann. Oper. Res..
[34] Anil K. Jain,et al. Artificial neural networks for feature extraction and multivariate data projection , 1995, IEEE Trans. Neural Networks.
[35] S. Morgenthaler. Robustness in Statistics , 2001 .
[36] Gintautas Dzemyda,et al. Large Datasets Visualization with Neural Network Using Clustered Training Data , 2008, ADBIS.
[37] Kwok Yip Szeto,et al. Community Detection Through Optimal Density Contrast of Adjacency Matrix , 2011, Informatica.
[38] Jacob Zahavi,et al. Using simulated annealing to optimize the feature selection problem in marketing applications , 2006, Eur. J. Oper. Res..
[39] Raimondo Manca,et al. HIV Evolution: A Quantification of the Effects Due to Age and to Medical Progress , 2011, Informatica.
[40] Jack P. C. Kleijnen,et al. Response surface methodology's steepest ascent and step size revisited , 2004, Eur. J. Oper. Res..
[41] Alan Jessop. An optimising approach to alternative clustering schemes , 2010, Central Eur. J. Oper. Res..
[42] Emmanuel Monfrini,et al. A Quadratic Loss Multi-Class SVM for which a Radius-Margin Bound Applies , 2011, Informatica.
[43] Adil M. Bagirov,et al. Modified global k-means algorithm for minimum sum-of-squares clustering problems , 2008, Pattern Recognit..
[44] Edmundas K. Zavadskas,et al. Multiattribute Selection from Alternative Designs of Infrastructure Components for Accidental Situations , 2009, Comput. Aided Civ. Infrastructure Eng..
[45] J. Tenenbaum,et al. A global geometric framework for nonlinear dimensionality reduction. , 2000, Science.
[46] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[47] M. Brusco,et al. Variable Neighborhood Search Heuristics for Selecting a Subset of Variables in Principal Component Analysis , 2009 .
[48] A. Tversky,et al. Judgment under Uncertainty: Heuristics and Biases , 1974, Science.
[49] Gintautas Dzemyda,et al. Topology Preservation Measures in the Visualization of Manifold-Type Multidimensional Data , 2009, Informatica.
[50] Gintautas Dzemyda,et al. Optimization of the Local Search in the Training for SAMANN Neural Network , 2006, J. Glob. Optim..
[51] Michael W. Trosset. Multidimensional Scaling Algorithms for Large Data Sets , 2005 .
[52] Edmundas Kazimieras Zavadskas,et al. Model for a Complex Analysis of Intelligent Built Environment , 2010 .
[53] Michael A. Saunders,et al. Atomic Decomposition by Basis Pursuit , 1998, SIAM J. Sci. Comput..
[54] Teuvo Kohonen,et al. Self-Organizing Maps, Third Edition , 2001, Springer Series in Information Sciences.
[55] Tamara Munzner,et al. Steerable, Progressive Multidimensional Scaling , 2004, IEEE Symposium on Information Visualization.
[56] Jacques Janssen,et al. Numerical Treatment of Homogeneous Semi-Markov Processes in Transient Case–a Straightforward Approach , 2004 .
[57] Mostafa El Qannari,et al. From Multiblock Partial Least Squares to Multiblock Redundancy Analysis. A Continuum Approach , 2011, Informatica.
[58] Robin Nunkesser,et al. An evolutionary algorithm for robust regression , 2010, Comput. Stat. Data Anal..
[59] Gintautas Dzemyda,et al. Visualization of a set of parameters characterized by their correlation matrix , 2001 .
[60] Peter Winker,et al. Applications of optimization heuristics to estimation and modelling problems , 2004, Comput. Stat. Data Anal..
[61] A. Naud,et al. Visualization of high-dimensional data using an association of multidimensional scaling to clustering , 2004, IEEE Conference on Cybernetics and Intelligent Systems, 2004..
[62] Stefano Benati,et al. Heuristic methods for the optimal statistic median problem , 2011, Comput. Oper. Res..
[63] R. Marshall. 5. Multidimensional Scaling. 2nd edn. Trevor F. Cox and Michael A. A. Cox, Chapman & Hall/CRC, Boca Raton, London, New York, Washington DC, 2000. No. of pages: xiv + 309. Price: $79.95. ISBN 1‐58488‐094‐5 , 2002 .
[64] Gintautas Dzemyda,et al. DIAGONAL MAJORIZATION ALGORITHM: PROPERTIES AND EFFICIENCY , 2007 .