Free Access
Issue
A&A
Volume 600, April 2017
Article Number A113
Number of page(s) 11
Section Cosmology (including clusters of galaxies)
DOI https://doi.org/10.1051/0004-6361/201629558
Published online 12 April 2017
  1. Arnouts, S., Cristiani, S., Moscardini, L., et al. 1999, MNRAS, 310, 540 [NASA ADS] [CrossRef] [Google Scholar]
  2. Beaumont., C., Williams, J., & Goodman, A. 2011, ApJ, 741, 14 [NASA ADS] [CrossRef] [Google Scholar]
  3. Benítez, N. 2000, ApJ, 536, 571 [NASA ADS] [CrossRef] [Google Scholar]
  4. Burges, C. 1998, Data Mining and Know Disc, 2, 2 [Google Scholar]
  5. Budavari, T., Szalay, A. S., Charlot, S., et al. 2005, ApJ, 619, L31 [NASA ADS] [CrossRef] [Google Scholar]
  6. Carrasco Kind, M., & Brunner, R. 2013, MNRAS, 432, 2 [NASA ADS] [CrossRef] [Google Scholar]
  7. Carliles, S., Budavari, T., Heinis, S., Priebe, C., & Szalay, A. S. 2010, ApJ, 712, 511 [NASA ADS] [CrossRef] [Google Scholar]
  8. Cassata, P., Guzzo, L., Franceschini, A., et al. 2007, ApJS, 172, 270 [NASA ADS] [CrossRef] [Google Scholar]
  9. Chang, C., & Lin, C. 2011, LIBSVM: a library for support vector machines, ACM Transactions on Intelligent Systems and Technology, 2,1 [Google Scholar]
  10. Collister, A., & Lahav, O. 2004, PASP, 116, 345 [NASA ADS] [CrossRef] [Google Scholar]
  11. Cortes, C., & Vapnik, V. 1995, Machine Learning, 20, 3 [Google Scholar]
  12. Davis, M., Guhathakurta, P., Konidaris, N. P., et al. 2007, ApJ, 660, L1 [NASA ADS] [CrossRef] [Google Scholar]
  13. Gerdes, D., Sypniewski, A. J., McKay, T. A., et al. 2010, ApJ, 715, 823 [NASA ADS] [CrossRef] [Google Scholar]
  14. Graham, A., & Driver, S. 2005, PASA, 22, 118 [NASA ADS] [CrossRef] [Google Scholar]
  15. Griffith, R., Cooper, M. C., Newman, J. A., et al. 2012, ApJS, 200, 9 [NASA ADS] [CrossRef] [Google Scholar]
  16. Gwyn, S. 2008, PASP, 120, 212 [NASA ADS] [CrossRef] [Google Scholar]
  17. Hassan., T., Mirabal, N., Contreras, J., & Oya, L. 2013, MNRAS, 428, 220 [NASA ADS] [CrossRef] [Google Scholar]
  18. Häussler, B., McIntosh, D. H., Barden, M., et al. 2007, ApJS, 172, 615 [NASA ADS] [CrossRef] [Google Scholar]
  19. Haykin, S. 1999, Neural Networks: A Comprehensive Foundation, Upper Saddle River (NJ: Prentice Hall) [Google Scholar]
  20. Hearin, A., Zentner, A., Ma, Z., & Huterer, D. 2010, ApJ, 720, 135 [NASA ADS] [CrossRef] [Google Scholar]
  21. Hearst, M., Scholköpf, B., Dumais, S., Osuna, E., & Platt, J. 1998, IEEE Int. Syst, 13, 18 [CrossRef] [Google Scholar]
  22. Hildebrandt, H., Arnouts, S., Capak, P., et al. 2010, A&A, 523, A31 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  23. Huretas-Company, M., Tasca, L., Rouan, D., et al. 2008, A&A, 497, 743 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  24. Hsu, C.-W., & Lin, C.-J. 2002, IEEE Trans Neural Net, 13, 2 [CrossRef] [Google Scholar]
  25. Huterer, D., Takada, M., Bernstein, G., & Jain, B. 2006, MNRAS, 366, 101 [NASA ADS] [CrossRef] [Google Scholar]
  26. Ilbert, O., Arnouts, S., McCracken, H. J., et al. 2006, A&A, 457, 841 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  27. Ivezic, Z., Tyson, J. A., Abel, B., et al. 2008, ArXiv e-prints [arXiv:0805.2366] [Google Scholar]
  28. Jolliffe, I. 2002, Principal Component Analysis. Series: Springer Series in Statistics, 2nd edn. (New York: Springer) [Google Scholar]
  29. Klement, R. J., Bailer-Jones, C. A. L., Fuchs, B., Rix, H.-W., & Smith, K. W. 2011, ApJ, 726, 103 [NASA ADS] [CrossRef] [Google Scholar]
  30. Knerr, S., Personnaz, L., & Dreyfyus, G. 1990, in Neurocomputing: Algorithms, Architectures, and Applications (Springer) [Google Scholar]
  31. Koekemoer, A., Aussel, H., Calzetti, D., et al. 2007, ApJS, 172, 196 [NASA ADS] [CrossRef] [Google Scholar]
  32. Laigle, C., McCracken, H. J., Ilbert, O., et al. 2016, ApJS, 224, 24 [NASA ADS] [CrossRef] [Google Scholar]
  33. Lilly, S., Le Brun, V., Maier, C., et al. 2009, ApJS, 184, 218 [NASA ADS] [CrossRef] [Google Scholar]
  34. Li, I., & Yee, H. 2008, AJ, 135, 809 [NASA ADS] [CrossRef] [Google Scholar]
  35. Lotz, J. M., Davis, M., Faber, S. M., et al. 2008, ApJ, 672, 177 [NASA ADS] [CrossRef] [Google Scholar]
  36. Malek, K., Solarz, A., Pollo, A., et al. 2013, A&A, 557, A16 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  37. Marton, G., Toth, L., Paladini, M., et al. 2016, MNRAS, 458, 347 [NASA ADS] [CrossRef] [Google Scholar]
  38. Momcheva, I. G., Brammer, G. B., van Dokkum, P. G., et al. 2016, ApJS, 225, 27 [NASA ADS] [CrossRef] [Google Scholar]
  39. Peng, C., Ho, L., Impev, C., & Rix, H. 2002, AJ, 124, 266 [NASA ADS] [CrossRef] [Google Scholar]
  40. Platt, J. 1998, Microsoft Technical Report, MSR-TR-98-14 [Google Scholar]
  41. Scarlata, C., Carollo, C. M., Lilly, S., et al. 2007, ApJS, 172, 406 [NASA ADS] [CrossRef] [Google Scholar]
  42. Scoville, A., Aussel, H., Brusa, M., et al. 2007, ApJS, 172, 1 [NASA ADS] [CrossRef] [Google Scholar]
  43. Singal, J., Shmakova, M., Gerke, B., Griffith, R. L., & Lotz, J. 2011, PASP, 123, 615 [NASA ADS] [CrossRef] [Google Scholar]
  44. Solarz, A., Pollo, A., Takeuchi, T. T., et al. 2012, A&A, 541, A50 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  45. Tagliaferri, R., Longo, G., Andreon, S., et al. 2003, Lect. Notes Comp. Sci., 2859, 226 [NASA ADS] [CrossRef] [Google Scholar]
  46. Vanzella, E., Cristiani, S., Fontana, A., et al. 2004, A&A, 423, 761 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  47. Vince, O., & Csabai, I. 2007, Toward more precise photometric redshift estimation, Proc. International Astronomical Union, 241, 573 [Google Scholar]
  48. Wadadekar, Y. 2004, PASP, 117, 79 [NASA ADS] [CrossRef] [Google Scholar]
  49. Wang, D., Zhang, Y., Liu, C., & Zhao, Y. 2007, CJAA, 7, 43 [Google Scholar]
  50. Way, M., & Srivastava, A. 2006, ApJ, 647, 102 [NASA ADS] [CrossRef] [Google Scholar]
  51. Wolf, C. 2009, MNRAS, 397, 520 [NASA ADS] [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.