C. Bishop, Pattern recognition and machine learning, 2006.

J. Bradley and C. Guestrin, Learning tree conditional random fields, ICML, 2010.

S. Branson, C. Wah, F. Schroff, B. Babenko, P. Welinder et al., Visual Recognition with Humans in the Loop, ECCV, 2010.
DOI : 10.1007/978-3-642-15561-1_32

M. Choi, J. Lim, A. Torralba, and A. Willsky, Exploiting hierarchical context on a large database of object categories, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010.
DOI : 10.1109/CVPR.2010.5540221

C. Chow and C. Liu, Approximating discrete probability distributions with dependence trees, IEEE Transactions on Information Theory, vol.14, issue.3, pp.462-467, 1968.
DOI : 10.1109/TIT.1968.1054142

J. Deng, A. Berg, K. Li, and F. Li, What Does Classifying More Than 10,000 Image Categories Tell Us?, ECCV, 2010.
DOI : 10.1007/978-3-642-15555-0_6

C. Desai, D. Ramanan, and C. Fowlkes, Discriminative models for multi-class object layout, ICCV, 2009.

D. Grangier and S. Bengio, A Discriminative Kernel-Based Approach to Rank Images from Text Queries, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.30, issue.8, pp.1371-1384, 2008.
DOI : 10.1109/TPAMI.2007.70791

M. Guillaumin, T. Mensink, J. Verbeek, and C. Schmid, TagProp: Discriminative metric learning in nearest neighbor models for image auto-annotation, 2009 IEEE 12th International Conference on Computer Vision, 2009.
DOI : 10.1109/ICCV.2009.5459266

URL : https://hal.archives-ouvertes.fr/inria-00439276

M. Huiskes and M. Lew, The MIR flickr retrieval evaluation, Proceeding of the 1st ACM international conference on Multimedia information retrieval, MIR '08, 2008.
DOI : 10.1145/1460096.1460104

C. Lampert, H. Nickisch, and S. Harmeling, Learning to detect unseen object classes by between-class attribute transfer, 2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009.
DOI : 10.1109/CVPR.2009.5206594

S. Nowak and M. Huiskes, New strategies for image annotation: Overview of the photo annotation task at ImageCLEF 2010, Working Notes of CLEF, 2010.

F. Perronnin, J. Sánchez, and T. Mensink, Improving the Fisher Kernel for Large-Scale Image Classification, ECCV, 2010.
DOI : 10.1007/978-3-642-15561-1_11

URL : https://hal.archives-ouvertes.fr/inria-00548630

J. Platt, Probabilities for SV machines, Advances in Large Margin Classifiers, 2000.

A. Rabinovich, A. Vedaldi, C. Galleguillos, E. Wiewiora, and S. Belongie, Objects in Context, 2007 IEEE 11th International Conference on Computer Vision, 2007.
DOI : 10.1109/ICCV.2007.4408986

B. Settles, Active learning literature survey, 2009.

I. Tsochantaridis, T. Joachims, T. Hofmann, and Y. Altun, Large margin methods for structured and interdependent output variables, JMLR, vol.6, pp.1453-1484, 2005.

S. Vijayanarasimhan and K. Grauman, Multi-level active prediction of useful image annotations for recognition, NIPS, 2009.

J. Weston, S. Bengio, and N. Usunier, Large scale image annotation: learning??to??rank with??joint word-image embeddings, ECML, 2010.
DOI : 10.1007/s10994-010-5198-3

J. Zhang, M. Marsza?ek, S. Lazebnik, and C. Schmid, Local Features and Kernels for Classification of Texture and Object Categories: A Comprehensive Study, International Journal of Computer Vision, vol.36, issue.1, pp.213-238, 2007.
DOI : 10.1007/s11263-006-9794-4

URL : https://hal.archives-ouvertes.fr/inria-00548574