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REFERENCES

  1. G. Bell, J. Gray and A. Szalay, IEEE Computer 39, 110 (2006).

  2. G. Bell, T. Hey and A. Szalay, Science 323, 1297 (2009).

  3. T. Hey, S. Tansley and K. Talle (eds.), The Fourth Paradigm: Data-Intensive Scientific Discovery (Microsoft Research, Redmond, WA, 2009).

  4. D. J. Hand, Statistical Science 21, p. 1 (2006).

  5. I. H. Witten and E. Frank, Data Mining: Practical Machine Learning Tools and Techniques, Morgan Kaufmann Series in Data Management Systems, 2nd edn. (Morgan Kaufmann, San Francisco, 2005).

  6. C. M. Bishop, Pattern Recognition and Machine Learning (Springer, New York, 2007).

  7. T. Hastie, R. Tibshirani and J. Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Springer Series in Statistics, 2nd edn. (Springer, New York, 2009).

  8. K. Borne, Scientific Data Mining in Astronomy, Data Mining and Knowledge Discovery Series Data Mining and Knowledge Discovery Series, (Taylor & Francis: CRC Press, Boca Raton, FL, 2009), pp. 91-114.

  9. D. C. Wells, E. W. Greisen and R. H. Harten, A&AS 44, p. 363 (1981).

  10. F. Ochsenbein et al., VOTable: Tabular Data for the Virtual Observatory, in Toward an International Virtual Observatory, eds. P. J. Quinn and K. M. Górski (2004).

  11. D. Pyle, Data Preparation for Data Mining, Morgan Kaufmann Series in Data Management Systems (Morgan Kaufmann, San Francisco, 1999).

  12. D. W. Hogg, preprint, [arXiv/0807.4820] (2008).

  13. K. Karhunen, Annales Academiae Scientiarum Fennicae Series A. I. Mathematica-Physica 37, 3 (1947).

  14. M. M. Loève, Fonctions Aléatoires de Second Ordre, in Processus Stochastiques et Mouvement Brownien, ed. P. Levy (Hermann, Paris, 1948), Paris.

  15. I. T. Jolliffe, Principal Component Analysis, Springer Series in Statistics, 2nd edn. (Springer, New York, 2002).

  16. S. Arya, D. M. Mount, N. S. Netanyahu, R. Silverman and A. Y. Wu, Journal of the Association for Computing Machinery 45, 891 (1998).

  17. N. Tishby, F. C. Pereira and W. Bialek, The Information Bottleneck Method, in The 37th annual Allerton Conference on Communication, Control, and Computing, 1999.

  18. R. A. Fisher, Annals of Eugenics 7, 179 (1936).

  19. A. Hyvärinen, J. Karhunen and E. Oja, Independent Component Analysis (John Wiley & Sons, New York, 2001).

  20. S. J. Lilly et al., ApJS 172, 70 (2007).

  21. D. G. York et al., AJ 120, 1579 (2000).

  22. W. Jeffrey and R. Rosner, ApJ 310, 473 (1986).

  23. C. M. Bishop, Neural Networks for Pattern Recognition (Oxford University Press, Oxford, 1995).

  24. B. D. Ripley, Pattern Recognition and Neural Networks (Cambridge University Press, Cambridge, UK, 2008).

  25. R. O. Duda, P. E. Hart and D. G. Stork, Pattern Classification, 2nd edn. (Cambridge University Press, Cambridge, UK, 2000).

  26. W. S. McCulloch and W. H. Pitts, Bulletin of Mathematical Biophysics 5, 115 (1943).

  27. J. J. Hopfield and D. W. Tank, Science 233, 625 (1986).

  28. P. J. Werbos, Beyond regression: new tools for prediction and analysis in the behavioural sciences, PhD thesis, Harvard, (Cambridge, MA, 1974).

  29. D. B. Parker, Learning Logic, Tech. Rep. TR-47, Center for Computational Research in Economics and Management Science, MIT (Cambridge, MA, 1985).

  30. D. E. Rumelhart, G. E. Hinton and R. J. Williams, Nature 323, 533 (1986).

  31. K. Levenberg, Quarterly of Applied Mathematics 2, p. 164 (1944).

  32. D. W. Marquardt, Journal of the Society of Industrial and Applied Mathematics 2, p. 431 (1963).

  33. A. E. Firth, O. Lahav and R. S. Somerville, MNRAS 339, 1195 (2003).

  34. J. N. Morgan and J. A. Sonquist, Journal of the American Statistical Association 58, 415 (1963).

  35. L. Breiman, J. Friedman, R. Olshen and C. Stone, Classification and Regression Trees (Wadsworth, 1984).

  36. J. R. Quinlan, Machine Learning 1, p. 81 (1986).

  37. J. R. Quinlan, C4.5: Programs for Machine Learning (Morgan Kaufmann, San Francisco, 1993).

  38. L. Rokach and O. Maimon, Data Mining with Decision Trees: Theory and Applications (World Scientific, New York, 2008).

  39. S. Salzberg, R. Chandar, H. Ford, S. K. Murthy and R. White, PASP 107, 279 (1995).

  40. C. Cortes and V. Vapnik, Machine Learning 20, 273 (1995).

  41. C. J. C. Burges, Knowledge Discovery and Data Mining 2, 121 (1998).

  42. V. Vapnik, The Nature of Statistical Learning Theory, 2nd edn. (Springer, New York, 1999).

  43. N. Cristianini and J. Shawe-Taylor, An Introduction to Support Vector Machines and Other Kernel-based Learning Methods (Cambridge University Press, 2000).

  44. V. Kecman, Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models (MIT Press, Cambridge, MA, 2001).

  45. B. Schlkopf and A. J. Smola, Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (MIT Press, Cambridge, MA, 2001).

  46. S. Abe, Support Vector Machines for Pattern Classification (Springer, New York, 2005).

  47. L. Wang, Support Vector Machines: Theory and Applications (Springer, New York, 2005).

  48. I. Steinwart and A. Christmann, Support Vector Machines (Springer, New York, 2008).

  49. M. A. Aizerman, E. M. Braverman and L. I. Rozonoer, Automation and Remote Control 25, 1175 (1964).

  50. M. Huertas-Company, D. Rouan, L. Tasca, G. Soucail and O. Le Fèvre, A&A 478, 971 (2008).

  51. E. Fix and J. Hodges Jr., Discriminatory analysis: non-parametric discrimination: Consistency properties., Tech. Rep. Report No. 4, USAF School of Aviation Medicine (Randolph Field, TX, 1951).

  52. T. M. Cover and P. E. Hart, IEEE Transactions on Information Theory 13, 21 (1967).

  53. D. W. Aha, D. Kibler and M. K. Albert, Machine Learning 6, 37 (1991).

  54. B. Dasarathy, Nearest Neighbor Pattern Classification Techniques (IEEE Computer Society Press, New York, 1991).

  55. G. Shakhnarovich, T. Darrell and P. Indyk (eds.), Nearest-Neighbor Methods in Learning and Vision: Theory and Practice (MIT Press, Cambridge, MA, 2006).

  56. E. Parzen, Annals of Mathematical Statistics 33, 1065 (1962).

  57. R. O. Duda and P. E. Hart, Pattern Classification and Scene Analysis (John Wiley, New York, 1973).

  58. B. W. Silverman, Density Estimation for Statistics and Data Analysis, Monographs on Statistics and Applied Probability (CRC Press, Boca Raton, FL, 1986).

  59. D. W. Scott, Multivariate Density Estimation: Theory, Practice, and Visualization, Wiley Series in Probability and Statistics (Wiley-Interscience, New York, 1992).

  60. C. Taylor, Vistas in Astronomy 41, 411 (1997).

  61. L. Wasserman, All of Statistics: a Concise Course in Statistics (Springer, New York, 2005).

  62. J. Klemelä, Smoothing of Multivariate Data: Density Estimation and Visualization, Wiley Series in Probability and Statistics (John Wiley & Sons, New York, 2009).

  63. H. Steinhaus, Bull. Acad. Polon. Sci. 4, 801 (1956).

  64. J. MacQueen, Some Methods for Classification and Analysis of Multivariate Observations, in Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, eds. L. M. LeCam and J. Neyman (University of California Press, Berkeley, 1967).

  65. D. M. Titterington, A. F. M. Smith and U. E. Makov, Statistical Analysis of Finite Mixture Distributions (John Wiley, New York, 1985).

  66. G. J. McLachlan and D. Peel, Finite Mixture Models, Wiley Series in Probability and Statistics (Wiley-Interscience, New York, 2000).

  67. A. J. Connolly, C. Genovese, A. W. Moore, R. C. Nichol, J. Schneider and L. Wasserman, preprint, [arXiv:astro-ph/0008187] (2000).

  68. J. Dolence and R. J. Brunner, Fast Two-Point Correlations of Extremely Large Data Sets, The 9th LCI International Conference on High-Performance Clustered Computing, Urbana-Champaign, IL, (2008).

  69. A. Dempster, N. Laird and D. Rubin, Journal of the Royal Statistical Society B 39, 1 (1977).

  70. M. Watanabe and K. Yamaguchi (eds.), The EM Algorithm and Related Statistical Models, Statistics: a Series of Textbooks and Monographs (CRC Press, Boca Raton, FL, 2003).

  71. G. J. McLachlan and T. Krishnan, The EM Algorithm and Extensions, Wiley Series in Probability and Statistics (John Wiley & Sons, New York, 2008).

  72. T. Kohonen, Biological Cybernetics 43, 59 (1982).

  73. T. Kohonen, Self-Organizing Maps, 3rd extended edition, Springer Series in Information Sciences, Vol. 30, 3rd edn. (Springer, Berlin, 2001).

  74. A. Naim, K. U. Ratnatunga and R. E. Griffiths, ApJS 111, p. 357 (1997).

  75. T. Kohonen, Self-Organization and Associative Memory, 3rd edn. (Springer-Verlag, Berlin, 1989).

  76. P. Comon, Signal Processing 36, 287 (1994).

  77. T. Lee, Independent Component Analysis - Theory and Applications (Kluwer Academic Publishers, New York, 1998).

  78. S. Roberts and R. Everson (eds.), Independent Component Analysis: Principles and Practice (Cambridge University Press, Cambridge, UK, 2001).

  79. J. V. Stone, Independent Component Analysis: A Tutorial Introduction (MIT Press, Cambridge, MA, 2004).

  80. O. Chapelle, B. Schölkopf and A. Zien (eds.), Semi-Supervised Learning (MIT Press, Cambridge, MA, 2006).

  81. X. Zhu, A. Goldberg, R. Brachman and T. Dietterich, Introduction to Semi-supervised Learning, Synthesis Lectures on Artificial Intelligence and Machine Learning (Morgan & Claypool, San Rafael, CA, 2009).

  82. D. Bazell and D. J. Miller, ApJ 618, 723 (2005).

  83. J. H. Holland, Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence (The University of Michigan Press, Ann Arbor, MI, 1975).

  84. D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning (Addison-Wesley, Reading, MA, 1989).

  85. D. A. Coley, An Introduction to Genetic Algorithms for Scientists and Engineers (World Scientific, New York, 1997).

  86. M. Mitchell, An Introduction to Genetic Algorithms (MIT Press, Cambridge, MA, 1998).

  87. R. L. Haupt and S. E. Haupt, Practical Genetic Algorithms, 2nd edn. (Wiley Inter-Science, New York, 2004).

  88. S. N. Sivanandam and S. N. Deepa, Introduction to Genetic Algorithms (Springer, New York, 2007).

  89. Goldberg, D. E., Design of innovation: Lessons from and for competent genetic algorithms (Kluwer Academic Publishers, Boston, MA, 2002).

  90. J. M. Adamo, Data Mining for Association Rules and Sequential Patterns: Sequential and Parallel Algorithms (Springer, New York, 2000).

  91. C. Zhang and S. Zhang, Association Rule Mining: Models and Algorithms, Lecture Notes in Computer Science (Springer, New York, 2002).

  92. Y. Benjamini and Y. Hochberg, Journal of the Royal Statistical Society B 57, 289 (1995).

  93. M. Welge, W. H. Hsu, L. S. Auvil, T. M. Redman and D. Tcheng, High-Performance Knowledge Discovery and Data Mining Systems Using Workstation Clusters, in 12th National Conference on High Performance Networking and Computing (SC99), 1999.

  94. S. L. Salzberg, Data Mining and Knowledge Discovery 1, 1 (1995).

  95. S. Kirkpatrick, C. D. Gelatt and M. P. Vecchi, Science 220, 671 (1983).

  96. V. Cerný, Journal of Optimization Theory and Applications 45, 41 (1985).

  97. P. J. van Laarhiven and E. H. Aarts, Simulated Annealing: Theory and Applications (Springer, New York, 1987).

  98. E. Aarts and J. Korst, Simulated Annealing and Boltzmann Machines: A Stochastic Approach to Combinatorial Optimization and Neural Computing (Wiley, New York, 1989).

  99. L. Breiman, Machine Learning 26, 123 (1996).

  100. L. Breiman, Machine Learning 45, 5 (2001).

  101. J. L. Bentley, Communications of the ACM 18, 509 (1975).

  102. J. P. Gardner, A. Connolly and C. McBride, Enabling rapid development of parallel tree search applications, in CLADE '07: Proceedings of the 5th IEEE workshop on Challenges of large applications in distributed environments, (ACM, New York, 2007).

  103. A. S. Miller, Vistas in Astronomy 36, 141 (1993).

  104. O. Lahav, A. Naim, L. Sodré and M. C. Storrie-Lombardi, MNRAS 283, p. 207 (1996).

  105. C. A. L. Bailer-Jones, R. Gupta and H. P. Singh, An Introduction to Artificial Neural Networks, in Automated Data Analysis in Astronomy, eds. R. Gupta, H. P. Singh and C. A. L. Bailer-Jones (2002).

  106. L.-L. Li, Y.-X. Zhang, Y.-H. Zhao and D.-W. Yang, Progress in Astronomy 24, 285 (2006).

  107. R. Tagliaferri et al., Neural Networks, 16, 297 (2003).

  108. R. L. White, Astronomical Applications of Oblique Decision Trees, American Institute of Physics Conference Series Vol. 1082 (2008).

  109. P. Charbonneau, ApJS 101, p. 309 (1995).

  110. C. A. L. Bailer-Jones, Automated Stellar Classification for Large Surveys: A Review of Methods and Results, in Automated Data Analysis in Astronomy, eds. R. Gupta, H. P. Singh and C. A. L. Bailer-Jones (2002).

  111. N. Weir, U. M. Fayyad, S. G. Djorgovski and J. Roden, PASP 107, p. 1243 (1995).

  112. M. C. Burl, L. Asker, P. Smyth, U. Fayyad, P. Perona, J. Aubele and L. Crumpler, Machine Learning 30, 165 (1998).

  113. M. C. Burl, C. Fowlkes, J. Roden, A. Stechert and S. Mukhtar, Diamond Eye: a distributed architecture for image data mining, Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series Vol. 3695 (1999).

  114. C. Kamath, Journal of Physics Conference Series 125, 012094 (2008).

  115. C. Kamath, Scientific data mining: a practical perspective (Society for Industrial and Applied Mathematics, Philadelphia, PA, 2009).

  116. S. J. Maddox, G. Efstathiou, W. J. Sutherland and J. Loveday, MNRAS 243, 692 (1990).

  117. S. G. Djorgovski, R. R. Gal, S. C. Odewahn, R. R. de Carvalho, R. Brunner, G. Longo and R. Scaramella, The Palomar Digital Sky Survey (DPOSS), in Wide Field Surveys in Cosmology, eds. S. Colombi, Y. Mellier and B. Raban (1998).

  118. S. C. Odewahn, E. B. Stockwell, R. L. Pennington, R. M. Humphreys and W. A. Zumach, AJ 103, 318 (1992).

  119. S. C. Odewahn and M. L. Nielsen, Vistas in Astronomy 38, 281 (1994).

  120. D. Bazell and Y. Peng, ApJS 116, p. 47 (1998).

  121. S. Andreon, G. Gargiulo, G. Longo, R. Tagliaferri and N. Capuano, MNRAS 319, 700 (2000).

  122. N. S. Philip, Y. Wadadekar, A. Kembhavi and K. B. Joseph, A&A 385, 1119 (2002).

  123. S. C. Odewahn, R. R. de Carvalho, R. R. Gal, S. G. Djorgovski, R. Brunner, A. Mahabal, P. A. A. Lopes, J. L. K. Moreira and B. Stalder, AJ 128, 3092 (2004).

  124. A. Collister et al., MNRAS 375, 68 (2007).

  125. N. Weir, U. M. Fayyad and S. Djorgovski, AJ 109, p. 2401 (1995).

  126. N. M. Ball, R. J. Brunner, A. D. Myers and D. Tcheng, ApJ 650, p. 497 (2006).

  127. D.-M. Qin, P. Guo, Z.-Y. Hu and Y.-H. Zhao, Chinese Journal of Astronomy and Astrophysics 3, 277 (2003).

  128. A. S. Miller and M. J. Coe, MNRAS 279, 293 (1996).

  129. E. P. Hubble, ApJ 64, 321 (1926).

  130. E. P. Hubble, Realm of the Nebulae (Yale University Press, Newhaven, CT, 1936).

  131. A. Sandage, The Hubble atlas of galaxies (Carnegie Institution, Washington, DC, 1961).

  132. A. Sandage and J. Bedke, The Carnegie atlas of galaxies (Carnegie Institution of Washington with The Flintridge Foundation, Washington, DC, 1994).

  133. S. van den Bergh, Galaxy morphology and classification (Cambridge University Press, Cambridge, UK, 1998).

  134. A. Sandage, ARA&A 43, 581 (2005).

  135. M. S. Roberts and M. P. Haynes, ARA&A 32, 115 (1994).

  136. C. Firmani and V. Avila-Reese, Physical processes behind the morphological Hubble sequence, Revista Mexicana de Astronomia y Astrofisica Conference Series Vol. 17 (2003).

  137. W. W. Morgan, PASP 70, p. 364 (1958).

  138. W. W. Morgan, PASP 71, p. 394 (1959).

  139. G. de Vaucouleurs, Qualitative and Quantitative Classifications of Galaxies., in Evolution of Galaxies and Stellar Populations, eds. B. M. Tinsley and R. B. Larson (1977).

  140. G. de Vaucouleurs, Annales d'Astrophysique 11, p. 247 (1948).

  141. F. S. Patterson, Harvard College Observatory Bulletin 914, 9 (1940).

  142. K. C. Freeman, ApJ 160, p. 811 (1970).

  143. J. L. Sérsic, Atlas de galaxias australes (Observatorio Astronomico, Cordoba, Argentina, 1968).

  144. A. W. Graham and S. P. Driver, PASA 22, 118 (2005).

  145. S. van den Bergh, ApJ 131, p. 215 (1960).

  146. S. van den Bergh, ApJ 131, p. 558 (1960).

  147. S. van den Bergh, ApJ 206, 883 (1976).

  148. C. J. Conselice, ApJS 147, 1 (2003).

  149. G. de Vaucouleurs, Memoirs of the Commonwealth Observatory, Mount Stromlo 3 (1956).

  150. G. de Vaucouleurs, Handbuch der Physik 53, p. 275 (1959).

  151. M. Barden, K. Jahnke and B. Häußler, ApJS 175, 105 (2008).

  152. M. C. Storrie-Lombardi, O. Lahav, L. Sodré and L. J. Storrie-Lombardi, MNRAS 259, p. 8P (1992).

  153. O. Lahav et al., Science 267, 859 (1995).

  154. A. Naim et al., MNRAS 274, 1107 (1995).

  155. A. Naim, O. Lahav, L. Sodré and M. C. Storrie-Lombardi, MNRAS 275, 567 (1995).

  156. A. A. Collister and O. Lahav, PASP 116, 345 (2004).

  157. A. Naim, K. U. Ratnatunga and R. E. Griffiths, ApJ 476, p. 510 (1997).

  158. D. S. Madgwick, MNRAS 338, 197 (2003).

  159. S. C. Odewahn, R. A. Windhorst, S. P. Driver and W. C. Keel, ApJ 472, p. L13 (1996).

  160. R. Windhorst, S. Odewahn, C. Burg, S. Cohen and I. Waddington, Ap&SS 269, 243 (1999).

  161. S. H. Cohen, R. A. Windhorst, S. C. Odewahn, C. A. Chiarenza and S. P. Driver, AJ 125, 1762 (2003).

  162. S. C. Odewahn, S. H. Cohen, R. A. Windhorst and N. S. Philip, ApJ 568, 539 (2002).

  163. D. Bazell and D. W. Aha, ApJ 548, 219 (2001).

  164. D. Bazell, MNRAS 316, 519 (2000).

  165. N. M. Ball, J. Loveday, M. Fukugita, O. Nakamura, S. Okamura, J. Brinkmann and R. J. Brunner, MNRAS 348, 1038 (2004).

  166. N. M. Ball, J. Loveday, R. J. Brunner, I. K. Baldry and J. Brinkmann, MNRAS 373, 845 (2006).

  167. N. M. Ball, J. Loveday and R. J. Brunner, MNRAS 383, 907 (2008).

  168. B. C. Kelly and T. A. McKay, AJ 129, 1287 (2005).

  169. M. Serra-Ricart, X. Calbet, L. Garrido and V. Gaitan, AJ 106, 1685 (1993).

  170. A. Adams and A. Woolley, Vistas in Astronomy 38, 273 (1994).

  171. E. Molinari and R. Smareglia, A&A 330, 447 (1998).

  172. P. A. M. de Theije and P. Katgert, A&A 341, 371 (1999).

  173. E. Cantú-Paz and C. Kamath, Evolving Neural Networks For The Classification Of Galaxies, in GECCO '02: Proceedings of the Genetic and Evolutionary Computation Conference, (Morgan Kaufmann Publishers Inc., San Francisco, 2002).

  174. C. Kamath, E. Cantú-Paz, I. K. Fodor and N. I. Tang, Computing in Science and Engineering 4, 52 (2002).

  175. R. H. Becker, R. L. White and D. J. Helfand, ApJ 450, p. 559 (1995).

  176. J. de la Calleja and O. Fuentes, MNRAS 349, 87 (2004).

  177. G. Spiekermann, AJ 103, 2102 (1992).

  178. E. A. Owens, R. E. Griffiths and K. U. Ratnatunga, MNRAS 281, 153 (1996).

  179. Y. Zhang, L. Li and Y. Zhao, MNRAS 392, 233 (2009).

  180. M. Huertas-Company et al., A&A 497, 743 (2009).

  181. P. Tsalmantza et al., A&A 470, 761 (2007).

  182. C. J. Lintott et al., MNRAS 389, 1179 (2008).

  183. M. L. Humason, ApJ 83, p. 10 (1936).

  184. W. W. Morgan and N. U. Mayall, PASP 69, p. 291 (1957).

  185. A. J. Connolly, A. S. Szalay, M. A. Bershady, A. L. Kinney and D. Calzetti, AJ 110, p. 1071 (1995).

  186. A. J. Connolly and A. S. Szalay, AJ 117, 2052 (1999).

  187. D. Madgwick, O. Lahav, K. Taylor and The 2dFGRS Team, Parameterisation of Galaxy Spectra in the 2dF Galaxy Redshift Survey, in Mining the Sky, eds. A. J. Banday, S. Zaroubi and M. Bartelmann (2001).

  188. C. W. Yip et al., AJ 128, 585 (2004).

  189. M. C. Storrie-Lombardi, M. J. Irwin, T. von Hippel and L. J. Storrie-Lombardi, Vistas in Astronomy 38, 331 (1994).

  190. S. R. Folkes, O. Lahav and S. J. Maddox, MNRAS 283, 651 (1996).

  191. M. Colless et al., preprint, [arXiv:astro-ph/0306581] (2003).

  192. N. Slonim, R. Somerville, N. Tishby and O. Lahav, MNRAS 323, 270 (2001).

  193. H. Lu, H. Zhou, J. Wang, T. Wang, X. Dong, Z. Zhuang and C. Li, AJ 131, 790 (2006).

  194. F. B. Abdalla, A. Mateus, W. A. Santos, L. Sodrè, Jr., I. Ferreras and O. Lahav, MNRAS 387, 945 (2008).

  195. A. Lauberts and E. A. Valentijn, The surface photometry catalogue of the ESO-Uppsala galaxies (European Southern Observatory, Garching, Germany, 1989).

  196. J. A. Baldwin, M. M. Phillips and R. Terlevich, PASP 93, 5 (1981).

  197. R. Carballo, A. S. Cofiño and J. I. González-Serrano, MNRAS 353, 211 (2004).

  198. J.-F. Claeskens, A. Smette, L. Vandenbulcke and J. Surdej, MNRAS 367, 879 (2006).

  199. R. Carballo, J. I. González-Serrano, C. R. Benn and F. Jiménez-Luján, MNRAS 391, 369 (2008).

  200. R. L. White et al., ApJS 126, 133 (2000).

  201. A. A. Suchkov, R. J. Hanisch and B. Margon, AJ 130, 2439 (2005).

  202. Y.-X. Zhang and Y.-H. Zhao, Chinese Journal of Astronomy and Astrophysics 7, 289 (2007).

  203. Y. Zhang, Y. Zhao and D. Gao, Advances in Space Research 41, 1949 (2008).

  204. Y. Zhao and Y. Zhang, Advances in Space Research 41, 1955 (2008).

  205. C. Knigge, S. Scaringi, M. R. Goad and C. E. Cottis, MNRAS 386, 1426 (2008).

  206. C. W. Yip et al., AJ 128, 2603 (2004).

  207. Y. Zhang and Y. Zhao, PASP 115, 1006 (2003).

  208. D. Gao, Y.-X. Zhang and Y.-H. Zhao, MNRAS 386, 1417 (2008).

  209. R. D'Abrusco, G. Longo and N. A. Walton, MNRAS 396, 223 (2009).

  210. G. T. Richards et al., ApJS 180, 67 (2009).

  211. M.-F. Zhao, C. Wu, A. Luo, F.-C. Wu and Y.-H. Zhao, Chinese Astronomy and Astrophysics 31, 352 (2007).

  212. S. P. Bamford, A. L. Rojas, R. C. Nichol, C. J. Miller, L. Wasserman, C. R. Genovese and P. E. Freeman, MNRAS 391, 607 (2008).

  213. J. F. Jarvis and J. A. Tyson, AJ 86, 476 (1981).

  214. P. B. Stetson, PASP 99, 191 (1987).

  215. E. Bertin and S. Arnouts, A&AS 117, 393 (1996).

  216. D. Maino et al., MNRAS 334, 53 (2002).

  217. F. Guglielmetti, R. Fischer and V. Dose, MNRAS 396, 165 (2009).

  218. M. Serra-Ricart, V. Gaitan, L. Garrido and I. Perez-Fournon, A&AS 115, p. 195 (1996).

  219. J. Goebel, J. Stutz, K. Volk, H. Walker, F. Gerbault, M. Self, W. Taylor and P. Cheeseman, A&A 222, L5 (1989).

  220. T. A. McGlynn et al., ApJ 616, 1284 (2004).

  221. D. Bazell, D. J. Miller and M. SubbaRao, ApJ 649, 678 (2006).

  222. W. W. Morgan, P. C. Keenan and E. Kellman, An atlas of stellar spectra, with an outline of spectral classification (The University of Chicago press, 1943).

  223. T. von Hippel, L. J. Storrie-Lombardi, M. C. Storrie-Lombardi and M. J. Irwin, MNRAS 269, p. 97 (1994).

  224. W. B. Weaver and A. V. Torres-Dodgen, ApJ 487, p. 847 (1997).

  225. H. P. Singh, R. K. Gulati and R. Gupta, MNRAS 295, 312 (1998).

  226. C. A. L. Bailer-Jones, M. Irwin and T. von Hippel, MNRAS 298, 361 (1998).

  227. R. K. Gulati and L. Altamirano, Ap&SS 273, 73 (2000).

  228. M. Bazarghan and R. Gupta, Ap&SS 315, 201 (2008).

  229. R. Gupta, H. P. Singh, K. Volk and S. Kwok, ApJS 152, 201 (2004).

  230. M. Manteiga, I. Carricajo, A. Rodríguez, C. Dafonte and B. Arcay, AJ 137, 3245 (2009).

  231. P. R. Wozniak, S. J. Williams, W. T. Vestrand and V. Gupta, AJ 128, 2965 (2004).

  232. S. Bailey, C. Aragon, R. Romano, R. C. Thomas, B. A. Weaver and D. Wong, ApJ 665, 1246 (2007).

  233. W. Waniak, Experimental Astronomy 21, 151 (2006).

  234. M. Faundez-Abans, M. I. Ormeno and M. de Oliveira-Abans, A&AS 116, 395 (1996).

  235. A. Misra and S. J. Bus, Artificial Neural Network Classification of Asteroids in the Sloan Digital Sky Survey, in AAS/Division for Planetary Sciences Meeting Abstracts, 2008.

  236. T. Chattopadhyay, R. Misra, A. K. Chattopadhyay and M. Naskar, ApJ 667, 1017 (2007).

  237. S. Scaringi, A. J. Bird, D. J. Clark, A. J. Dean, A. B. Hill, V. A. McBride and S. E. Shaw, MNRAS 390, 1339 (2008).

  238. J. Stebbins and A. E. Whitford, ApJ 108, p. 413 (1948).

  239. W. A. Baum, Photoelectric Magnitudes and Red-Shifts, in IAU Symp. 15: Problems of Extra-Galactic Research, 1962.

  240. D. C. Koo, AJ 90, 418 (1985).

  241. E. D. Loh and E. J. Spillar, ApJ 303, 154 (1986).

  242. S. D. J. Gwyn and F. D. A. Hartwick, ApJ 468, p. L77 (1996).

  243. K. M. Lanzetta, A. Yahil and A. Fernandez-Soto, Nature 381, 759 (1996).

  244. B. Mobasher, M. Rowan-Robinson, A. Georgakakis and N. Eaton, MNRAS 282, L7 (1996).

  245. M. J. Sawicki, H. Lin and H. K. C. Yee, AJ 113, 1 (1997).

  246. A. J. Connolly, A. S. Szalay and R. J. Brunner, ApJ 499, p. L125 (1998).

  247. Y. Wang, N. Bahcall and E. L. Turner, AJ 116, 2081 (1998).

  248. N. Benítez, ApJ 536, 571 (2000).

  249. D. C. Koo, Overview - Photometric Redshifts: A Perspective from an Old-Timer[!] on their Past, Present, and Potential, in Photometric Redshifts and the Detection of High Redshift Galaxies, eds. R. Weymann, L. Storrie-Lombardi, M. Sawicki and R. Brunner, Astronomical Society of the Pacific Conference Series, Vol. 191 (1999).

  250. M. Massarotti, A. Iovino and A. Buzzoni, A&A 368, 74 (2001).

  251. R. J. Brunner, A. J. Connolly, A. S. Szalay and M. A. Bershady, ApJ 482, p. L21 (1997).

  252. E. Vanzella et al., A&A 423, 761 (2004).

  253. L.-L. Li, Y.-X. Zhang, Y.-H. Zhao and D.-W. Yang, Chinese Journal of Astronomy and Astrophysics 7, 448 (2007).

  254. R. D'Abrusco, A. Staiano, G. Longo, M. Brescia, M. Paolillo, E. De Filippis and R. Tagliaferri, ApJ 663, 752 (2007).

  255. M. Banerji, F. B. Abdalla, O. Lahav and H. Lin, MNRAS 386, 1219 (2008).

  256. H. Oyaizu, M. Lima, C. E. Cunha, H. Lin, J. Frieman and E. S. Sheldon, ApJ 674, 768 (2008).

  257. M. D. Niemack, R. Jimenez, L. Verde, F. Menanteau, B. Panter and D. Spergel, ApJ 690, 89 (2009).

  258. Y. Wadadekar, PASP 117, 79 (2005).

  259. D. Wang, Y.-X. Zhang, C. Liu and Y.-H. Zhao, Chinese Journal of Astronomy and Astrophysics 8, 119 (2008).

  260. S. Carliles, T. Budavári, S. Heinis, C. Priebe and A. Szalay, Photometric Redshift Estimation on SDSS Data Using Random Forests, in Astronomical Data Analysis Software and Systems XVII, eds. R. W. Argyle, P. S. Bunclark and J. R. Lewis, Astronomical Society of the Pacific Conference Series, Vol. 394 (2008).

  261. N. M. Ball, R. J. Brunner, A. D. Myers, N. E. Strand, S. L. Alberts and D. Tcheng, ApJ 683, 12 (2008).

  262. A. J. Connolly, I. Csabai, A. S. Szalay, D. C. Koo, R. G. Kron and J. A. Munn, AJ 110, p. 2655 (1995).

  263. D. Sowards-Emmerd, J. A. Smith, T. A. McKay, E. Sheldon, D. L. Tucker and F. J. Castander, AJ 119, 2598 (2000).

  264. B. C. Hsieh, H. K. C. Yee, H. Lin and M. D. Gladders, ApJS 158, 161 (2005).

  265. P. A. A. Lopes, MNRAS 380, 1608 (2007).

  266. T. Budavári, A. S. Szalay, A. J. Connolly, I. Csabai and M. Dickinson, AJ 120, 1588 (2000).

  267. I. Csabai, A. J. Connolly, A. S. Szalay and T. Budavári, AJ 119, 69 (2000).

  268. I. Csabai et al., AJ 125, 580 (2003).

  269. N. Padmanabhan et al., MNRAS 359, 237 (2005).

  270. M. Brodwin et al., ApJ 651, 791 (2006).

  271. T. Budavári, ApJ 695, 747 (2009).

  272. T. Budavári et al., AJ 122, 1163 (2001).

  273. G. T. Richards et al., AJ 122, 1151 (2001).

  274. T. S. R. Babbedge et al., MNRAS 353, 654 (2004).

  275. M. A. Weinstein et al., ApJS 155, 243 (2004).

  276. X.-B. Wu, W. Zhang and X. Zhou, Chinese Journal of Astronomy and Astrophysics 4, 17 (2004).

  277. S. Kitsionas, E. Hatziminaoglou, A. Georgakakis and I. Georgantopoulos, A&A 434, 475 (2005).

  278. N. M. Ball, R. J. Brunner, A. D. Myers, N. E. Strand, S. Alberts, D. Tcheng and X. Llorà, ApJ 663, p. 774 (2007).

  279. N. D. Kumar, Machine learning techniques for astrophysical modelling and photometric redshift estimation of quasars in optical sky surveys, Master's thesis, Oxford University (2008).

  280. C. Wolf, MNRAS 397, 520 (2009).

  281. C. Wolf, L. Wisotzki, A. Borch, S. Dye, M. Kleinheinrich and K. Meisenheimer, A&A 408, 499 (2003).

  282. M. Salvato et al., ApJ 690, 1250 (2009).

  283. J. F. Ramírez, O. Fuentes and R. K. Gulati, Experimental Astronomy 12, 163 (2001).

  284. T. Solorio, O. Fuentes, R. Terlevich and E. Terlevich, MNRAS 363, 543 (2005).

  285. A. C. Becker, Astronomische Nachrichten 329, p. 280 (2008).

  286. S. G. Djorgovski, A. A. Mahabal, R. J. Brunner, R. R. Gal, S. Castro, R. R. de Carvalho and S. C. Odewahn, Searches for Rare and New Types of Objects, in Virtual Observatories of the Future, eds. R. J. Brunner, S. G. Djorgovski and A. S. Szalay, Astronomical Society of the Pacific Conference Series, Vol. 225 (2001).

  287. M. Bottino, A. J. Banday and D. Maino, MNRAS 389, 1190 (2008).

  288. S. Pires, J. B. Juin, D. Yvon, Y. Moudden, S. Anthoine and E. Pierpaoli, A&A 455, 741 (2006).

  289. N. G. Phillips and A. Kogut, preprint, [arXiv:astro-ph/0108234] (2001).

  290. D. J. Rohde, M. R. Gallagher, M. J. Drinkwater and K. A. Pimbblet, MNRAS 369, 2 (2006).

  291. M. Taylor and A. I. Diaz, On the Deduction of Galactic Abundances with Evolutionary Neural Networks, in From Stars to Galaxies: Building the Pieces to Build Up the Universe, eds. A. Vallenari, R. Tantalo, L. Portinari and A. Moretti, Astronomical Society of the Pacific Conference Series, Vol. 374 (2007).

  292. C. Bogdanos and S. Nesseris, Journal of Cosmology and Astro-Particle Physics 5, p. 6 (2009).

  293. R. Li, Y. Cui, H. He and H. Wang, Advances in Space Research 42, 1469 (2008).

  294. J. F. Mustard, L. Li and G. He, J. Geophys. Res. 103, 19419 (1998).

  295. G. Lemson and J. Zuther, Memorie della Societa Astronomica Italiana 80, 342 (2009).

  296. V. Springel et al., Nature 435, 629 (2005).

  297. R. Brun and F. Rademakers, Nuclear Instruments and Methods in Physics Research A 389, 81 (1997).

  298. T. Budavári and A. S. Szalay, ApJ 679, 301 (2008).

  299. C. E. Cunha, M. Lima, H. Oyaizu, J. Frieman and H. Lin, MNRAS 396, 2379 (2009).

  300. V. E. Margoniner and D. M. Wittman, ApJ 679, 31 (2008).

  301. D. Wittman, ApJ 700, L174 (2009).

  302. A. D. Myers, M. White and N. M. Ball, MNRAS 399, 2279 (2009).

  303. C. van Breukelen and L. Clewley, MNRAS 395, 1845 (2009).

  304. C. A. L. Bailer-Jones, K. W. Smith, C. Tiede, R. Sordo and A. Vallenari, MNRAS 391, 1838 (2008).

  305. J. Vaidya, C. Clifton and M. Zhu., Privacy Preserving Data Mining (Springer, New York, 2005).

  306. C. C. Aggarwal and P. S. Yu (eds.), Privacy-Preserving Data Mining: Models and Algorithms (Springer, New York, 2008).

  307. R. Scranton, A. J. Connolly, A. S. Szalay, R. H. Lupton, D. Johnston, T. Budavári, J. Brinkmann and M. Fukugita, preprint, [arXiv:astro-ph/0508564] (2005).

  308. Z. Ivezic, J. A. Tyson, R. Allsman, J. Andrew, R. Angel and for the LSST Collaboration, preprint, [arXiv/0805.2366] (2008).

  309. C. Donalek, A. Mahabal, S. G. Djorgovski, S. Marney, A. Drake, E. Glikman, M. J. Graham and R. Williams, New Approaches to Object Classification in Synoptic Sky Surveys, American Institute of Physics Conference Series Vol. 1082 (2008).

  310. A. H. Studenmund, Using Econometrics, 2nd edn. (Addison-Wesley, New York, 2005).

  311. A. Mahabal, S. G. Djorgovski, M. Turmon, J. Jewell, R. R. Williams, A. J. Drake, M. G. Graham, C. Donalek, E. Glikman and Palomar-QUEST team, Astronomische Nachrichten 329, 288 (2008).

  312. A. J. Drake, R. Williams, M. J. Graham, A. Mahabal, S. G. Djorgovski, R. R. White, W. T. Vestrand and J. Bloom, VOEventNet: An Open Source of Transient Alerts for Astronomers., Bulletin of the American Astronomical Society Vol. 38 (2007).

  313. Z. Ivezic et al., Parametrization and Classification of 20 Billion LSST Objects: Lessons from SDSS, American Institute of Physics Conference Series Vol. 1082 (2008).

  314. K. Borne, J. Becla, I. Davidson, A. Szalay and J. A. Tyson, The LSST Data Mining Research Agenda, American Institute of Physics Conference Series Vol. 1082 (2008).

  315. M. A. C. Perryman et al., A&A 369, 339 (2001).

  316. C. A. L. Bailer-Jones, A Method for Exploiting Domain Information in Astrophysical Parameter Estimation, in Astronomical Data Analysis Software and Systems XVII, eds. R. W. Argyle, P. S. Bunclark and J. R. Lewis, Astronomical Society of the Pacific Conference Series, Vol. 394 (2008).

  317. S. G. Djorgovski et al., Astronomische Nachrichten 329, p. 263 (2008).

  318. A. J. Drake et al., ApJ 696, 870 (2009).

  319. K. W. Hodapp et al., Astronomische Nachrichten 325, 636 (2004).

  320. S. Johnston et al., Publications of the Astronomical Society of Australia 24, 174 (2007).

  321. L. Eyer et al., Variability type classification of multi-epoch surveys, American Institute of Physics Conference Series Vol. 1082 (2008).

  322. M. C. Kaczmarczik, G. T. Richards, S. S. Mehta and D. J. Schlegel, AJ 138, 19 (2009).

  323. A. Mahabal et al., Towards Real-time Classification of Astronomical Transients, American Institute of Physics Conference Series Vol. 1082 (2008).

  324. G. E. Moore, Electronics 38, 114 (1965).

  325. D. A. Bader (ed.), Petascale Computing: Algorithms and Applications, Computational Science Series (CRC Press, Boca Raton, FL, 2007).

  326. G. Amdahl, Validity of the Single Processor Approach to Achieving Large-Scale Computing Capabilities, in Spring Joint Computer Conference, (AFIPS Press, Atlantic City, N.J., 1967).

  327. K. Ebcioglu, V. Saraswat and V. Sarkar, The IBM PERCS Project and New Opportunities for Compiler-Driven Performance via a New Programming Model, Compiler-Driven Performance Workshop (CASCON 2004), (2004).

  328. A. S. Szalay et al., GrayWulf: Scalable Clustered Architecture for Data Intensive Computing, Hawaii International Conference on System Sciences (IEEE Computer Society, Los Alamitos, CA, 2009).

  329. A. S. Szalay, J. Gray and Vandenberg, J., Petabyte Scale Data Mining: Dream or Reality?, SPIE Astronomy Telescopes and Instruments, Waikoloa, Hawaii, (2002).

  330. S. M. McConnell and D. B. Skillicorn, Distributed Data Mining for Astrophysical Datasets, in Astronomical Data Analysis Software and Systems XIV, eds. P. Shopbell, M. Britton and R. Ebert, Astronomical Society of the Pacific Conference Series, Vol. 347 (2005).

  331. A. A. Freitas and S. H. Lavington, Mining Very Large Databases with Parallel Processing (Kluwer Academic Publishers, 1998).

  332. H. Kargupta and P. Chan, Advances in Distributed and Parallel Knowledge Discovery (AAAI/MIT Press, Cambridge, MA, 2000).

  333. M. J. Zaki and C. Ho (eds.), Large-scale Parallel Data Mining, Lecture Notes in Artificial Intelligence, State-of-the-Art-Survey, Vol. 1759 (Springer, New York, 2002).

  334. K. Bhaduri, K. Liu, H. Kargupta and J. Ryan, Distributed Data Mining Bibliography Online bibliography, (2006).

  335. R. Jin, G. Yang and G. Agrawal, IEEE Transactions On Knowledge and Data Engineering 17, 71 (2005).

  336. N. Gray, The Fact and Future of Semantic Astronomy, in Astronomical Data Analysis Software and Systems XVII, eds. R. W. Argyle, P. S. Bunclark and J. R. Lewis, Astronomical Society of the Pacific Conference Series, Vol. 394 (2008).

  337. M. L. Norman, G. L. Bryan, R. Harkness, J. Bordner, D. Reynolds, B. O'Shea and R. Wagner, preprint, [arXiv/0705.1556] (2007).

  338. R. J. Brunner, V. Kindratenko and A. D. Myers, Developing and Deploying Advanced Algorithms to Novel Supercomputing Hardware, tech. rep., NASA (2007).

  339. E. L. Gomez, H. L. Gomez and J. Yardley, preprint, [arXiv/0903.0266] (2009).

  340. A. W. Moore et al., Fast Algorithms and Efficient Statistics: N-Point Correlation Functions, in Mining the Sky, eds. A. J. Banday, S. Zaroubi and M. Bartelmann (2001).

  341. D. Gao, Y. Zhang and Y. Zhao, The Application of kd-tree in Astronomy, in Astronomical Data Analysis Software and Systems XVII, eds. R. W. Argyle, P. S. Bunclark and J. R. Lewis, Astronomical Society of the Pacific Conference Series, Vol. 394 (2008).

  342. A. G. Gray, A. W. Moore, R. C. Nichol, A. J. Connolly, C. Genovese and L. Wasserman, Multi-Tree Methods for Statistics on Very Large Datasets in Astronomy, in Astronomical Data Analysis Software and Systems (ADASS) XIII, eds. F. Ochsenbein, M. G. Allen and D. Egret, Astronomical Society of the Pacific Conference Series, Vol. 314 (2004).

  343. Y. Shirasaki, M. Ohishi, Y. Mizumoto, M. Tanaka, S. Honda, M. Oe, N. Yasuda and Y. Masunaga, Structured Query Language for Virtual Observatory, in Astronomical Data Analysis Software and Systems XIV, eds. P. Shopbell, M. Britton and R. Ebert, Astronomical Society of the Pacific Conference Series, Vol. 347 (2005).

  344. S. Derriere et al., UCD in the IVOA context, in Astronomical Data Analysis Software and Systems (ADASS) XIII, eds. F. Ochsenbein, M. G. Allen and D. Egret, Astronomical Society of the Pacific Conference Series, Vol. 314 (2004).

  345. P. Dowler, S. Gaudet, D. Durand, R. Redman, N. Hill and S. Goliath, Common Archive Observation Model, in Astronomical Data Analysis Software and Systems XVII, eds. R. W. Argyle, P. S. Bunclark and J. R. Lewis, Astronomical Society of the Pacific Conference Series, Vol. 394 (2008).

  346. J. Gray, D. T. Liu, M. Nieto-Santisteban, A. S. Szalay, D. DeWitt and G. Heber, Scientific Data Management in the Coming Decade, Technical Report MSR-TR-2005-10, Microsoft Research (2005).

  347. J. Gray, A. S. Szalay, A. R. Thakar, P. Z. Kunszt, C. Stoughton, D. Slutz and J. vandenBerg, preprint, [arXiv:cs/0202014] (2002).

  348. C. Vignali, F. Fiore, A. Comastri, M. Brusa, R. Gilli, N. Cappelluti, F. Civano and G. Zamorani, Multi-wavelength data handling in current and future surveys: the possible role of Virtual Observatory, in Multi-wavelength Astronomy and Virtual Observatory, ed. D. Baines & P. Osuna (2009).

  349. E. A. González-Solares et al., MNRAS 388, 89 (2008).

  350. M. Brescia et al., Memorie della Societa Astronomica Italiana 80, p. 565 (2009).

  351. T. Kitching, A. Amara, A. Rassat and A. Refregier, preprint, [arXiv/0901.3143] (2009).

  352. I. V. Chilingarian, Virtual Observatory for Astronomers: Where Are We Now?, in Multi-wavelength Astronomy and Virtual Observatory, ed. D. Baines & P. Osuna (2009).

  353. W. B. Landsman, The IDL Astronomy User's Library, in Astronomical Data Analysis Software and Systems II, eds. R. J. Hanisch, R. J. V. Brissenden and J. Barnes, Astronomical Society of the Pacific Conference Series, Vol. 52 (1993).

  354. M. B. Taylor, TOPCAT & STIL: Starlink Table/VOTable Processing Software, in Astronomical Data Analysis Software and Systems XIV, eds. P. Shopbell, M. Britton and R. Ebert, Astronomical Society of the Pacific Conference Series, Vol. 347 (2005).

  355. M. Comparato, U. Becciani, A. Costa, B. Larsson, B. Garilli, C. Gheller and J. Taylor, PASP 119, 898 (2007).

  356. N. Urunkar, A. K. Kembhavi, A. Navelkar, J. Pandya, V. Moosani, P. Nair and M. Shaikh, Highlights of Astronomy 14, 620 (2007).

  357. J. D. Taylor, T. Boch, M. Comparato, M. Taylor, N. Winstanley and R. G. Mann, Binding Applications Together with PLASTIC, in Astronomical Data Analysis Software and Systems XVI, eds. R. A. Shaw, F. Hill and D. J. Bell, Astronomical Society of the Pacific Conference Series, Vol. 376 (2007).

  358. M. B. Taylor, STILTS - A Package for Command-Line Processing of Tabular Data, in Astronomical Data Analysis Software and Systems XV, eds. C. Gabriel, C. Arviset, D. Ponz and S. Enrique, Astronomical Society of the Pacific Conference Series, Vol. 351 (2006).

  359. M. Borkin, A. Goodman, M. Halle and D. Alan, Application of Medical Imaging Software to 3D Visualization of Astronomical Data, in Astronomical Data Analysis Software and Systems XVI, eds. R. A. Shaw, F. Hill and D. J. Bell, Astronomical Society of the Pacific Conference Series, Vol. 376 (2007).

  360. R. Scranton et al., preprint, [arXiv/0709.0752] (2007).

  361. D. G. Barnes, C. J. Fluke, P. D. Bourke and O. T. Parry, Publications of the Astronomical Society of Australia 23, 82 (2006).

  362. C. J. Fluke, D. G. Barnes and N. T. Jones, Publications of the Astronomical Society of Australia 26, 37 (2009).

  363. S. Levy, Interactive 3-D visualization of particle systems with Partiview, in Astrophysical Supercomputing using Particle Simulations, eds. J. Makino and P. Hut, IAU Symposium, Vol. 208 (2003).

  364. T. Szalay, V. Springel and G. Lemson, preprint, [arXiv/0811.2055] (2008).

  365. P. Hut, Virtual Laboratories and Virtual Worlds, IAU Symposium Vol. 246 (2008).

  366. T. Ebisuzaki, J. Makino, T. Fukushige, M. Taiji, D. Sugimoto, T. Ito and S. K. Okumura, PASJ 45, 269 (1993).

  367. E. Gaburov, S. Harfst and S. Portegies Zwart, New Astronomy 14, 630 (2009).

  368. R. G. Belleman, J. Bédorf and S. F. Portegies Zwart, New Astronomy 13, 103 (2008).

  369. S. Ord, L. Greenhill, R. Wayth, D. Mitchell, K. Dale, H. Pfister and R. G. Edgar, preprint, [arXiv/0902.0915] (2009).

  370. V. Garcia, E. Debreuve and M. Barlaud, preprint, [arXiv/0804.1448] (2008).

  371. S. D. Brown, R. J. Francis, J. Rose and Z. G. Vranesic, Field-Programmable Gate Arrays, The Springer International Series in Engineering and Computer Science (Springer, New York, 1992).

  372. D. Buell, T. El-Ghazawi, K. Gaj and V. Kindratenko, Computer 40, 23 (2007).

  373. E. Won, Nuclear Instruments and Methods in Physics Research A 581, 816 (2007).

  374. M. Freeman, M. Weeks and J. Austin, Hardware implementation of similarity functions, in IADIS AC, 2005.

  375. M. Scarpino, Programming the Cell Processor: For Games, Graphics, and Computation (Prentice Hall PTR, New York, 2008).

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