Free Access
Issue
A&A
Volume 632, December 2019
Article Number A56
Number of page(s) 18
Section Catalogs and data
DOI https://doi.org/10.1051/0004-6361/201936006
Published online 27 November 2019
  1. Abolfathi, B., Aguado, D., Aguilar, G., et al. 2018, ApJS, 235, 42 [NASA ADS] [CrossRef] [Google Scholar]
  2. Abraham, S., Philip, N., Kembhavi, A., Wadadekar, Y. G., & Sinha, R. 2012, MNRAS, 419, 80 [NASA ADS] [CrossRef] [Google Scholar]
  3. Agnello, A., & Spiniello, C. 2019, MNRAS, 489, 2525 [NASA ADS] [CrossRef] [Google Scholar]
  4. Agnello, A., Kelly, B. C., Treu, T., & Marshall, P. J. 2015, MNRAS, 448, 1446 [NASA ADS] [CrossRef] [Google Scholar]
  5. Agnello, A., Sonnenfeld, A., Suyu, S. H., et al. 2016, MNRAS, 458, 3830 [NASA ADS] [CrossRef] [Google Scholar]
  6. Agnello, A., Schechter, P. L., Morgan, N. D., et al. 2018a, MNRAS, 475, 2086 [NASA ADS] [CrossRef] [Google Scholar]
  7. Agnello, A., Lin, H., Kuropatkin, N., et al. 2018b, MNRAS, 479, 4345 [NASA ADS] [CrossRef] [Google Scholar]
  8. Akhmetov, V., Fedorov, P., Velichko, A., & Shulga, V. 2017, MNRAS, 469, 763 [NASA ADS] [Google Scholar]
  9. Anguita, T., Schmidt, R. W., Turner, E. L., et al. 2008, A&A, 480, 327 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  10. Anguita, T., Schechter, P. L., Kuropatkin, N., et al. 2018, MNRAS, 480, 5017 [NASA ADS] [Google Scholar]
  11. Assef, R. J., Stern, D., Kochanek, C. S., et al. 2013, ApJ, 772, 26 [NASA ADS] [CrossRef] [Google Scholar]
  12. Bachchan, R. K., Hobbs, D., & Lindegren, L. 2016, A&A, 589, A71 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  13. Bai, Y., Liu, J., Wang, S., & Yang, F. 2019, AJ, 157, 9 [NASA ADS] [CrossRef] [Google Scholar]
  14. Baldry, I. K., Liske, J., Brown, M. J. I., et al. 2018, MNRAS, 474, 3875 [NASA ADS] [CrossRef] [Google Scholar]
  15. Ball, N. M., Brunner, R. J., Myers, A. D., & Tcheng, D. 2006, ApJ, 650, 497 [NASA ADS] [CrossRef] [Google Scholar]
  16. Barrientos, F., Pichara, K., Troncoso, P., et al. 2018, VST in the Era of the Large Sky Surveys, 9 [Google Scholar]
  17. Bate, N. F., Floyd, D. J. E., Webster, R. L., & Wyithe, J. S. B. 2011, ApJ, 731, 71 [NASA ADS] [CrossRef] [Google Scholar]
  18. Blanton, M., Bershady, M., Abolfathi, B., et al. 2017, AJ, 154, 28 [NASA ADS] [CrossRef] [Google Scholar]
  19. Braibant, L., Hutsemékers, D., Sluse, D., Anguita, T., & García-Vergara, C. J. 2014, A&A, 565, L11 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  20. Breiman, L. 2001, Mach. Learn., 45, 5 [CrossRef] [Google Scholar]
  21. Brescia, M., Cavuoti, S., & Longo, G. 2015, MNRAS, 450, 3893 [NASA ADS] [CrossRef] [Google Scholar]
  22. Cabanac, R. A., Alard, C., Dantel-Fort, M., et al. 2007, A&A, 461, 813 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  23. Carrasco, D., Barrientos, L., Pichara, K., et al. 2015, A&A, 584, A44 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  24. Capaccioli, M., & Schipani, P. 2011, The Messenger, 146, 2 [NASA ADS] [Google Scholar]
  25. Capaccioli, M., Schipani, P., de Paris, G., et al. 2012, Science from the Next Generation Imaging and Spectroscopic Surveys, 1 [Google Scholar]
  26. Chen, T., & Guestrin, C. 2016, Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 785 [CrossRef] [Google Scholar]
  27. Chiu, K., Richards, G., Hewett, P., & Maddox, N. 2007, MNRAS, 375, 1180 [NASA ADS] [CrossRef] [Google Scholar]
  28. Cortes, C., & Vapnik, V. 1995, Mach. Learn., 20, 273 [Google Scholar]
  29. Cutri, R., Wright, E., Conrow, T., et al. 2013, Explanatory Supplement to the AllWISE Data Release Products, Tech. rep. [Google Scholar]
  30. D’Isanto, A., Cavuoti, S., Gieseke, F., & Polsterer, K. 2018, A&A, 616, A97 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  31. de Jong, J. T. A., Verdoes Kleijn, G. A., Kuijken, K. H., & Valentijn, E. A. 2013, Exp. Astron., 35, 25 [NASA ADS] [CrossRef] [Google Scholar]
  32. de Jong, J. T. A., Verdoes Kleijn, G. A., Erben, T., et al. 2017, A&A, 604, A134 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  33. Ding, X., Treu, T., Suyu, S. H., et al. 2017, MNRAS, 465, 4634 [NASA ADS] [CrossRef] [Google Scholar]
  34. Donley, J. L., Koekemoer, A. M., Brusa, M., et al. 2012, ApJ, 748, 142 [NASA ADS] [CrossRef] [Google Scholar]
  35. Dorogush, A. V., Ershov, V., & Gulin, A. 2018, ArXiv e-prints [arXiv:1810.11363] [Google Scholar]
  36. Driver, S. P., Norberg, P., Baldry, I. K., et al. 2009, Geophys., 50, 12 [Google Scholar]
  37. Duda, R. O., & Hart, P. E. 1973, Pattern Classification and Scene Analysis (J. Wiley & Sons) [Google Scholar]
  38. Edge, A., Sutherland, W., Kuijken, K., et al. 2013, The Messenger, 154, 32 [NASA ADS] [Google Scholar]
  39. Elting, C., Bailer-Jones, C. A. L., & Smith, K. W. 2008, Am. Inst. Phys. Conf. Ser., 1082, 9 [NASA ADS] [Google Scholar]
  40. Elvis, M., Wilkes, B. J., McDowell, J. C., et al. 1994, ApJS, 95, 1 [NASA ADS] [CrossRef] [Google Scholar]
  41. Eyer, L., & Blake, C. 2005, MNRAS, 358, 30 [NASA ADS] [CrossRef] [Google Scholar]
  42. Friedman, J. H. 2000, Ann. Stat., 29, 1189 [CrossRef] [Google Scholar]
  43. Gaia Collaboration (Brown, A., et al.) 2018a, A&A, 616, A1 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  44. Gaia Collaboration (Mignard, F., et al.) 2018b, A&A, 616, A14 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  45. Gieseke, F., Polsterer, K. L., Thom, A., et al. 2011, 2010 Ninth International Conference on Machine Learning and Applications, 352 [Google Scholar]
  46. Gilman, D., Birrer, S., Treu, T., Keeton, C. R., & Nierenberg, A. 2018, MNRAS, 481, 819 [NASA ADS] [CrossRef] [Google Scholar]
  47. Guerras, E., Mediavilla, E., Jimenez-Vicente, J., et al. 2013, ApJ, 778, 123 [NASA ADS] [CrossRef] [Google Scholar]
  48. Guo, S., Qi, Z., Liao, S., et al. 2018, A&A, 618, A144 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  49. Hartley, P., Flamary, R., Jackson, N., Tagore, A. S., & Metcalf, R. B. 2017, MNRAS, 471, 3378 [NASA ADS] [CrossRef] [Google Scholar]
  50. Haehnelt, M. G., & Kauffmann, G. 2000, MNRAS, 318, L35 [NASA ADS] [CrossRef] [Google Scholar]
  51. Hernitschek, N., Schlafly, E., Branimir, S., et al. 2016, ApJ, 817, 73 [NASA ADS] [CrossRef] [Google Scholar]
  52. Hopkins, P. F., Hernquist, L., Cox, T. J., Robertson, B., & Springel, V. 2006, ApJS, 163, 50 [NASA ADS] [CrossRef] [Google Scholar]
  53. Ivezić, Ž, & LSST Science Collaboration 2013, LSST Science Requirements Document, http://ls.st/LPM-17 [Google Scholar]
  54. Jacobs, C., Collett, T., Glazebrook, K., et al. 2019, MNRAS, 484, 5330 [NASA ADS] [CrossRef] [Google Scholar]
  55. Jarrett, T. H., Cohen, M., Masci, F., et al. 2011, ApJ, 735, 112 [NASA ADS] [CrossRef] [Google Scholar]
  56. Jin, X., Zhang, Y., & Zhang, J. 2019, MNRAS, 485, 4539 [NASA ADS] [CrossRef] [Google Scholar]
  57. Kauffmann, G., & Haehnelt, M. 2000, MNRAS, 311, 576 [NASA ADS] [CrossRef] [Google Scholar]
  58. Keeton, C. R., & Moustakas, L. A. 2009, ApJ, 699, 1720 [NASA ADS] [CrossRef] [Google Scholar]
  59. Khramtsov, V., & Akhmetov, V. 2018, Proceedings of a IEEE XIIIth International Scientific and Technical Conference “CSIT”, 72 [Google Scholar]
  60. Khramtsov, V., Akhmetov, V., & Fedorov, P. 2018, A&A, submitted [Google Scholar]
  61. Kim, D.-W., Protopapas, P., Byun, Y.-I., et al. 2011, ApJ, 735, 68 [NASA ADS] [CrossRef] [Google Scholar]
  62. Kovács, A., & Szapudi, I. 2015, MNRAS, 448, 1305 [NASA ADS] [CrossRef] [Google Scholar]
  63. Krakowski, T., Małek, K., Bilicki, M., et al. 2016, A&A, 596, A39 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  64. Krakowski, T., Małek, K., Bilicki, M., Siudek, M., & Pollo, A. 2018, Polish Astron. Soc., 7, 252 [Google Scholar]
  65. Kochanek, C. S. 2006, in Gravitational Lensing: Strong, Weak and Micro, eds. G. Meylan, P. Jetzer, & P. North (Berlin: Springer-Verlag) [Google Scholar]
  66. Koopmans, L. V. E., Treu, T., Bolton, A. S., Burles, S., & Moustakas, L. A. 2006, ApJ, 649, 599 [NASA ADS] [CrossRef] [Google Scholar]
  67. Koopmans, L. V. E., Bolton, A., Treu, T., et al. 2009, ApJ, 703, L51 [NASA ADS] [CrossRef] [Google Scholar]
  68. Krone-Martins, A., Delchambre, L., Wertz, O., et al. 2018, A&A, 616, L11 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  69. Kuijken, K. 2008, A&A, 482, 1053 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  70. Kuijken, K., Heymans, C., Hildebrandt, H., et al. 2015, MNRAS, 454, 3500 [NASA ADS] [CrossRef] [Google Scholar]
  71. Kuijken, K., Heymans, C., Dvornik, A., et al. 2019, A&A, 625, A2 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  72. Lacy, M., Storrie-Lombardi, L. J., Sajina, A., et al. 2004, ApJS, 154, 166 [NASA ADS] [CrossRef] [Google Scholar]
  73. Lanusse, F., Ma, Q., Li, N., et al. 2018, MNRAS, 473, 3895 [NASA ADS] [CrossRef] [Google Scholar]
  74. Laureijs, R., Amiaux, J., Arduini, S., et al. 2011, ArXiv e-prints [arXiv:1110.3193] [Google Scholar]
  75. Liao, K., Ding, X., Biesiada, M., Fan, X.-L., & Zhu, Z.-H. 2018, ApJ, 867, 69 [NASA ADS] [CrossRef] [Google Scholar]
  76. Lindegren, L., Hernandez, J., Bombrun, A., et al. 2018, A&A, 616, A2 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  77. Lemon, C. A., Auger, M. W., McMahon, R. G., & Koposov, S. E. 2017, MNRAS, 472, 5023 [NASA ADS] [CrossRef] [Google Scholar]
  78. Lemon, C., Auger, M., McMahon, R., & Ostrovski, F. 2018, MNRAS, 479, 5060 [NASA ADS] [CrossRef] [Google Scholar]
  79. Mansour, Y. 1997, Proceedings of the 14th International Conference on Machine Learning, 195 [Google Scholar]
  80. Mateos, S., Alonso-Herrero, A., Carrera, F. J., et al. 2012, MNRAS, 426, 3271 [NASA ADS] [CrossRef] [Google Scholar]
  81. Matthews, B. 1975, Biochim. Biophys. Acta (BBA)– Protein Struct., 405, 442 [CrossRef] [Google Scholar]
  82. Metcalf, R. B., Meneghetti, M., Avestruz, C., et al. 2018, A&A, 625, A119 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  83. Motta, V., Mediavilla, E., Falco, E., & Muñoz, J. A. 2012, ApJ, 755, 82 [NASA ADS] [CrossRef] [Google Scholar]
  84. Nakoneczny, S., Bilicki, M., Solarz, A., et al. 2019, A&A, 624, A13 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  85. Nolte, A., Wang, L., Bilicki, M., Holwerda, B., & Biehl, M. 2019, Neurocomputing, 342, 172 [CrossRef] [Google Scholar]
  86. Oguri, M., & Marshall, P. J. 2010, MNRAS, 405, 2579 [NASA ADS] [Google Scholar]
  87. Oguri, M., Inada, N., Pindor, B., et al. 2006, AJ, 132, 999 [NASA ADS] [CrossRef] [Google Scholar]
  88. Oguri, M., Rusu, C. E., & Falco, E. E. 2014, MNRAS, 439, 2494 [NASA ADS] [CrossRef] [Google Scholar]
  89. Ostrovski, F., Lemon, C., Auger, M., et al. 2018, MNRAS, 473, L116 [NASA ADS] [CrossRef] [Google Scholar]
  90. Paraficz, D., Courbin, F., Tramacere, A., et al. 2016, A&A, 592, A75 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  91. Peters, C. M., Richards, G. T., Myers, A. D., et al. 2015, ApJ, 811, 95 [NASA ADS] [CrossRef] [Google Scholar]
  92. Petrillo, C. E., Tortora, C., Chatterjee, S., et al. 2017, MNRAS, 472, 1129 [NASA ADS] [CrossRef] [Google Scholar]
  93. Petrillo, C. E., Tortora, C., Chatterjee, S., et al. 2019a, MNRAS, 482, 807 [NASA ADS] [Google Scholar]
  94. Petrillo, C. E., Tortora, C., Vernardos, G., et al. 2019b, MNRAS, 484, 3879 [NASA ADS] [CrossRef] [Google Scholar]
  95. Proft, S., & Wambsganss, J. 2015, A&A, 574, A46 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  96. Prokhorenkova, L., Gusev, G., Vorobev, A., Dorogush, A. V., & Gulin, A. 2018, Adv. Neural Inf. Process. Syst., 31, 6638 [Google Scholar]
  97. Quinlan, J. R. 1986, Mach. Learn., 1, 81 [Google Scholar]
  98. Refsdal, S. 1964, MNRAS, 128, 307 [NASA ADS] [CrossRef] [Google Scholar]
  99. Rumelhart, D. E., Hinton, G. E., & Williams, R. J. 1986, Parallel Distributed Processing: Explorations in the Microstructure of Cognition (Cambridge, MA, USA: MIT Press), 1, 318 [Google Scholar]
  100. Robin, A., Luri, X., Reylé, C., et al. 2012, A&A, 543, A100 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  101. Rusu, C. E., Oguri, M., Minowa, Y., et al. 2014, MNRAS, 444, 2561 [NASA ADS] [CrossRef] [Google Scholar]
  102. Rusu, C. E., Berghea, C. T., Fassnacht, C. D., et al. 2019, MNRAS, 486, 4987 [NASA ADS] [Google Scholar]
  103. Shankar, F., Weinberg, D. H., & Miralda-Escudé, J. 2009, ApJ, 690, 20 [NASA ADS] [CrossRef] [Google Scholar]
  104. Shen, Y., Strauss, M. A., Ross, N. P., et al. 2009, ApJ, 697, 1656 [NASA ADS] [CrossRef] [Google Scholar]
  105. Schechter, P. L., & Wambsganss, J. 2002, ApJ, 580, 685 [NASA ADS] [CrossRef] [Google Scholar]
  106. Schechter, P. L., Anguita, T., Morgan, N. D., Read, M., & Shanks, T. 2018, Res. Notes AAS, 2, 21 [NASA ADS] [CrossRef] [Google Scholar]
  107. Schindler, J.-T., Fan, X., McGreer, I. D., et al. 2017, ApJ, 851, 13 [NASA ADS] [CrossRef] [Google Scholar]
  108. Schindler, J.-T., Fan, X., McGreer, I. D., et al. 2018, ApJ, 863, 144 [NASA ADS] [CrossRef] [Google Scholar]
  109. Sergeyev, A., Spiniello, C., Khramtsov, V., et al. 2018, Res. Notes AAS, 2, 189 [NASA ADS] [CrossRef] [Google Scholar]
  110. Sluse, D., Schmidt, R., Courbin, F., et al. 2011, A&A, 528, A100 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  111. Spiniello, C., Koopmans, L. V. E., Trager, S. C., Czoske, O., & Treu, T. 2011, MNRAS, 417, 3000 [NASA ADS] [CrossRef] [Google Scholar]
  112. Spiniello, C., Koopmans, L. V. E., Trager, S. C., et al. 2015, MNRAS, 452, 2434 [NASA ADS] [CrossRef] [Google Scholar]
  113. Spiniello, C., Agnello, A., Napolitano, N. R., et al. 2018, MNRAS, 480, 1163 [NASA ADS] [CrossRef] [Google Scholar]
  114. Spiniello, C., Sergeyev, A., Marchetti, L., et al. 2019, MNRAS, 485, 5086 [NASA ADS] [Google Scholar]
  115. Stern, D., Eisenhardt, P., Gorjian, V., et al. 2005, ApJ, 631, 163 [NASA ADS] [CrossRef] [Google Scholar]
  116. Stern, D., Assef, R. J., Benford, D. J., et al. 2012, ApJ, 753, 30 [NASA ADS] [CrossRef] [Google Scholar]
  117. Suyu, S. H., Treu, T., Hilbert, S., et al. 2014, ApJ, 788, L35 [NASA ADS] [CrossRef] [Google Scholar]
  118. Suyu, S. H., Bonvin, V., Courbin, F., et al. 2017, MNRAS, 468, 2590 [NASA ADS] [CrossRef] [Google Scholar]
  119. Treu, T., Agnello, A., & Strides Team 2015, Am. Astron. Soc., 225, 318.04 [NASA ADS] [Google Scholar]
  120. Tinney, C. G. 1995, MNRAS, 277, 609 [NASA ADS] [CrossRef] [Google Scholar]
  121. Tinney, C. G., Da Costa, G. S., & Zinnecker, H. 1997, MNRAS, 285, 111 [NASA ADS] [CrossRef] [Google Scholar]
  122. Vakili, M., et al. 2019, MNRAS, in press [Google Scholar]
  123. Vapnik, V. 1995, The Nature of Statistical Learning Theory (New York, USA: Springer-Verlag) [CrossRef] [Google Scholar]
  124. Viquar, M., Basak, S., Dasgupta, A., Agrawal, S., & Saha, S. 2018, ArXiv e-prints [arXiv:1804.05051] [Google Scholar]
  125. Walsh, D., Carswell, R. F., & Weymann, R. J. 1979, Nature, 279, 381 [NASA ADS] [CrossRef] [PubMed] [Google Scholar]
  126. Werner, M. W., Roellig, T. L., Low, F. J., et al. 2004, ApJS, 154, 1 [NASA ADS] [CrossRef] [Google Scholar]
  127. Wright, E. L., Eisenhardt, P. R. M., Mainzer, A. K., et al. 2010, AJ, 140, 1868 [NASA ADS] [CrossRef] [Google Scholar]
  128. Wright, A. H., Hildebrandt, H., Kuijken, K., et al. 2019, A&A, 632, A34 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  129. Wyithe, J. S. B., & Loeb, A. 2003, ApJ, 595, 614 [NASA ADS] [CrossRef] [Google Scholar]
  130. Zackrisson, E., & Riehm, T. 2010, Adv. Astron., 2010, 478910 [NASA ADS] [CrossRef] [Google Scholar]

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