S. Boughorbel, J. P. Tarel, and N. Boujemaa, The intermediate matching kernel for image local features, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005., pp.889-894, 2005.
DOI : 10.1109/IJCNN.2005.1555970

L. Ertoz, M. Steinbach, and V. Kumar, A new shared nearest neighbor clustering algorithm and its applications, Workshop on Clustering High Dimensional Data and its Applications at 2nd SIAM International Conference on Data Mining, pp.105-115, 2002.

R. A. Jarvis and E. A. Patrick, Clustering using a similarity measure based on shared near neighbors. Computers, IEEE Transactions on, vol.100, issue.11, pp.1025-1034, 1973.

H. Jegou, M. Douze, and C. Schmid, Hamming Embedding and Weak Geometric Consistency for Large Scale Image Search, Computer Vision?ECCV, pp.304-317, 2008.
DOI : 10.1007/978-3-540-88682-2_24
URL : https://hal.archives-ouvertes.fr/inria-00316866

H. Jégou, F. Perronnin, M. Douze, and C. Schmid, Aggregating local image descriptors into compact codes. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.34, issue.9, pp.1704-1716, 2012.

A. Joly and O. Buisson, A posteriori multi-probe locality sensitive hashing, Proceeding of the 16th ACM international conference on Multimedia, MM '08, pp.209-218, 2008.
DOI : 10.1145/1459359.1459388

A. Joly and O. Buisson, Random maximum margin hashing, CVPR 2011, 2011.
DOI : 10.1109/CVPR.2011.5995709
URL : https://hal.archives-ouvertes.fr/hal-00642178

A. Joly, J. Champ, and O. Buisson, Instance-based bird species identication with undiscriminant features pruning-lifeclef 2014, p.2014, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01088798

M. Lasseck, Large-scale identification of birds in audio recordings, Working notes of CLEF 2014 conference, 2014.

V. Leveau, A. Joly, O. Buisson, and P. Valduriez, Kernelizing Spatially Consistent Visual Matches for Fine-Grained Classification, Proceedings of the 5th ACM on International Conference on Multimedia Retrieval, ICMR '15, p.2015, 2015.
DOI : 10.1145/2671188.2749328
URL : https://hal.archives-ouvertes.fr/hal-01145988

S. Lyu, Mercer kernels for object recognition with local features In: Computer Vision and Pattern Recognition, CVPR 2005. IEEE Computer Society Conference on, pp.223-229, 2005.

J. Mercer, Functions of positive and negative type, and their connection with the theory of integral equations. Philosophical transactions of the royal society of London. Series A, containing papers of a mathematical or physical character pp, pp.415-446, 1909.

F. Perronnin and C. Dance, Fisher Kernels on Visual Vocabularies for Image Categorization, 2007 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2007.
DOI : 10.1109/CVPR.2007.383266

J. Sivic and A. Zisserman, Video Google: a text retrieval approach to object matching in videos, Proceedings Ninth IEEE International Conference on Computer Vision, pp.1470-1477, 2003.
DOI : 10.1109/ICCV.2003.1238663

D. Stowell and M. D. Plumbley, Automatic large-scale classification of bird sounds is strongly improved by unsupervised feature learning, PeerJ, vol.16, issue.4, p.488, 2014.
DOI : 10.7717/peerj.488/supp-1

T. Tuytelaars, M. Fritz, K. Saenko, and T. Darrell, The NBNN kernel, 2011 International Conference on Computer Vision, pp.1824-1831, 2011.
DOI : 10.1109/ICCV.2011.6126449