Free Access
Issue
A&A
Volume 611, March 2018
Article Number A53
Number of page(s) 26
Section Numerical methods and codes
DOI https://doi.org/10.1051/0004-6361/201731305
Published online 29 March 2018
  1. Abdalla, F. B., Amara, A., Capak, P., et al. 2008, MNRAS, 387, 969 [NASA ADS] [CrossRef] [Google Scholar]
  2. Albrecht, A., Bernstein, G., Cahn, R., et al. 2006, ArXiv e-prints [arxiv:astro-ph/0609591] [Google Scholar]
  3. Baldry, I. K., Alpaslan, M., Bauer, A. E., et al. 2014, MNRAS, 441, 2440 [NASA ADS] [CrossRef] [Google Scholar]
  4. Benitez, N. 1999, in ASP Conf. Ser., 536, 571 [Google Scholar]
  5. Beutler, F., Blake, C., Colless, M., et al. 2011, MNRAS, 416, 3017 [NASA ADS] [CrossRef] [Google Scholar]
  6. Beutler, F., Blake, C., Colless, M., et al. 2012, MNRAS, 423, 3430 [NASA ADS] [CrossRef] [Google Scholar]
  7. Bolzonella, M., Miralles, J.-M., & Pelló, R. 2000, A&A, 363, 476 [NASA ADS] [Google Scholar]
  8. Brammer, G. B., van Dokkum, P. G., & Coppi, P. 2008, ApJS, 686, 1503 [NASA ADS] [CrossRef] [Google Scholar]
  9. Chandola, V., Banerjee, A., & Kumar, V. 2009, ACM Comput. Surv., 41, 15 [CrossRef] [Google Scholar]
  10. Collister, A. A., & Lahav, O. 2004, PASP, 116, 345 [NASA ADS] [CrossRef] [Google Scholar]
  11. Cool, R. J., Moustakas, J., Blanton, M. R., et al. 2013, ApJ, 767, 118 [NASA ADS] [CrossRef] [Google Scholar]
  12. Cristianini, N., & Shawe-Taylor, J. 2000, An Introduction to Support Vector Machines: and Other Kernel-based Learning Methods (Cambridge University Press) [CrossRef] [Google Scholar]
  13. Dietterich, T. G. 2000, in Multiple Classifier Systems (Springer), 1 [Google Scholar]
  14. Dietterich, T. G., & Bakiri, G. 1995, J. Artificial Intelligence Res., 2, 263 [Google Scholar]
  15. Fawcett, T. 2006, Pattern Recognition Lett., 27, 861 [CrossRef] [Google Scholar]
  16. Feldmann, R., Carollo, C. M., Porciani, C., et al. 2006, MNRAS, 372, 565 [NASA ADS] [CrossRef] [Google Scholar]
  17. Garilli, B., Fumana, M., Franzetti, P., et al. 2010, PASP, 122, 827 [NASA ADS] [CrossRef] [Google Scholar]
  18. Garilli, B., Guzzo, L., Scodeggio, M., et al. 2014, A&A, 562, A23 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  19. Green, J., Schechter, P., Baltay, C., et al. 2012, ArXiv e-prints [arxiv:1208.4012] [Google Scholar]
  20. Guzzo, L., Scodeggio, M., Garilli, B., et al. 2014, A&A 566, A108 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  21. Hastie, T., & Tibshirani, R. 1998, Annals Stat., 26, 451 [CrossRef] [Google Scholar]
  22. Huterer, D. 2002, Phys. Rev. D, 65, 3001 [NASA ADS] [CrossRef] [Google Scholar]
  23. Ilbert, O., Arnouts, S., McCracken, H. J., et al. 2006, A&A, 457, 841 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  24. Ivezic, Z., Tyson, J. A., Abel, B., et al. 2008, ArXiv e-prints [arxiv:0805.2366] [Google Scholar]
  25. Laureijs, R., Amiaux, J., Arduini, S., et al. 2011, ArXiv e-prints [arxiv:1110.3193] [Google Scholar]
  26. Le Fèvre, O., Vettolani, G., Garilli, B., et al. 2005, A&A, 439, 845 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  27. Le Fèvre, O., Cassata, P., Cucciati, O., et al. 2013, A&A, 559, A14 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  28. Le Fèvre, O., Tasca, L., Cassata, P., et al. 2015, A&A, 576, A79 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  29. Linder, E. V., & Jenkins, A. 2003, MNRAS, 346, 573 [NASA ADS] [CrossRef] [Google Scholar]
  30. Machado, D. P., Leonard, A., Starck, J.-L., Abdalla, F. B., & Jouvel, S. 2013, A&A, 560, A83 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  31. Patcha, A., & Park, J.-M. 2007, Computer Networks, 51, 3448 [NASA ADS] [CrossRef] [Google Scholar]
  32. Schuecker, P. 1993, ApJS, 84, 39 [NASA ADS] [CrossRef] [Google Scholar]
  33. Scodeggio, M., Franzetti, P., Garilli, B., et al. 2005, PASP, 117, 1284 [NASA ADS] [CrossRef] [Google Scholar]
  34. Shahid, M., Rossholm, A., Lovstrom, B., & Zepernick, H.-J. 2014, EURASIP J. Image Video Processing, 2014, 40 [CrossRef] [Google Scholar]
  35. Simkin, S. M. 1974, A&A, 31, 129 [NASA ADS] [Google Scholar]
  36. Tonry, J., & Davis, M. 1979, ApJ, 84, 1511 [NASA ADS] [CrossRef] [Google Scholar]
  37. Vapnik, V. N. 2000, The Nature of Statistical Learning Theory (Springer) [CrossRef] [Google Scholar]
  38. Wahba, G. 1998, Support Vector Machines, Reproducing Kernel Hilbert Spaces and the Randomized GACV(MIT Press) [Google Scholar]
  39. Wahba, G. 2002, PNAS, 99, 16524 [NASA ADS] [CrossRef] [Google Scholar]
  40. Wang, Y., Percival, W., Cimatti, A., et al. 2010, MNRAS, 409, 737 [NASA ADS] [CrossRef] [Google Scholar]
  41. Zoubian, J., Kümmel, M., Kermiche, S., et al. 2014, in ASP Conf. Ser., 485, 509 [Google Scholar]

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