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CPS2201 Mikhail L.
            References
            1.  Alekh Agarwal, Leon Bottou, Miroslav Dudik, and John Langford. Para-
               active learning. arXiv preprint arXiv:1310.8243, 2013.
            2.  Michael Ashikhmin and Peter Shirley. An anisotropic phong brdf model.
               Journal of graphics tools, 5 (2):25{32, 2000.
            3.  Alina Beygelzimer, Sanjoy Dasgupta, and John Langford. Importance
               weighted active learning. In Proceedings of the 26th Annual International
               Conference on Machine Learning, pages 49{56. ACM, 2009.
            4.  Adam Brady, Jason Lawrence, Pieter Peers, and Westley Weimer. genbrdf:
               Discovering new analytic brdfs with genetic programming. ACM Trans.
               Graph., 33(4):114:1{114:11, July 2014. ISSN 0730- 0301. doi:
               10.1145/2601097.2601193. URL
               http://doi.acm.org/10.1145/2601097.2601193.
            5.  Eric Brochu, Nando D Freitas, and Abhijeet Ghosh. Active preference
               learning with discrete choice data. In Advances in neural information
               processing systems, pages 409{416, 2008.
            6.  Robert L Cook and Kenneth E Torrance. A reectance model for computer
               graphics. In ACM Siggraph Computer Graphics, volume 15, pages
               307{316. ACM, 1981.
            7.  David Roxbee Cox and Nancy Reid. The theory of the design of
               experiments. CRC Press, 2000.
            8.  Sanjoy Dasgupta and Daniel Hsu. Hierarchical sampling for active
               learning. In Proceedings of the 25  international conference on Machine
                                                th
               learning, pages 208{215. ACM, 2008.
            9.  Katarina Z Doctor and Je_ M Byers. Optimal sampling of brdf's of varying
               complexity. In IGARSS 2018-2018 IEEE International Geoscience and
               Remote Sensing Symposium, pages 4123{4126. IEEE, 2018.
           10.  Pinar Donmez and Jaime G Carbonell. Proactive learning: cost-sensitive
               active learning with multiple imperfect oracles. In Proceedings of the 17th
               ACM conference on Information and knowledge management, pages
               619{628. ACM, 2008.
           11.  Sir Ronald Aylmer Fisher, Statistiker Genetiker, Ronald Aylmer Fisher,
               Statistician Genetician, Ronald Aylmer Fisher, and Statisticien G_en_eticien.
               The design of experiments, volume 12. Oliver and Boyd Edinburgh, 1960.
           12.  Xiao D He, Kenneth E Torrance, Fran_cois X Sillion, and Donald P
               Greenberg. A comprehensive physical model for light reection. In ACM
               SIGGRAPH Computer Graphics, volume 25, pages 175{186. ACM, 1991.
           13.  Andreas Hope and Kai-Olaf Hauer. Three-dimensional appearance
               characterization of diffuse standard reection materials. Metrologia,
               47(3):295, 2010. URL http://stacks.iop.org/0026-1394/47/i=3/a=021.
           14.  Solomon Kullback and Richard A Leibler. On information and su_ciency.
               The Annals of Mathematical Statistics, pages 79{86, 1951.

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