Y. Adini, Y. Moses, and S. Ullman, Face recognition: the problem of compensating for changes in illumination direction, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.19, issue.7, 1997.
DOI : 10.1109/34.598229

F. Bach, Active learning for misspecified generalized linear models, Advances in Neural Information Processing Systems (NIPS), 2006.

N. Belkin, Laplacian Eigenmaps for Dimensionality Reduction and Data Representation, Neural Computation, vol.15, issue.6, pp.1373-1396, 2003.
DOI : 10.1126/science.290.5500.2319

N. Belkin, Semi-supervised learning on manifolds, Machine Learning, pp.209-239, 2004.

N. Boujemaa, F. Fleuret, V. Gouet, and H. Sahbi, Visual content extraction for automatic semantic annotation of video news, the proceedings of the SPIE Conference, 2004.

G. Caenen and E. Pauwels, <title>Logistic regression model for relevance feedback in content-based image retrieval</title>, Storage and Retrieval for Media Databases 2002, pp.49-58, 2002.
DOI : 10.1117/12.451115

Y. Chen, X. Zhou, and T. Huang, One-class svm for learning in image retrieval, Int'l Conf on Image Processing, 2001.

I. Cox, M. Miller, T. Minka, and P. Yianilos, An optimized interaction strategy for Bayesian relevance feedback, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231), pp.553-558, 1998.
DOI : 10.1109/CVPR.1998.698660

Y. Fang and D. Geman, Experiments in Mental Face Retrieval, Proceedings AVBPA 2005, Lecture Notes in Computer Science, pp.637-646, 2005.
DOI : 10.1007/11527923_66

M. Ferecatu, M. Crucianu, and N. Boujemaa, Retrieval of difficult image classes using svd-based relevance feedback, Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval , MIR '04, pp.23-30, 2004.
DOI : 10.1145/1026711.1026716

M. Hein and J. Audibert, Intrinsic dimensionality estimation of submanifolds in euclidean space, Proceedings of the 22nd Internatical Conference on Machine Learning (ICML), pp.289-296, 2005.

M. Hein, J. Audibert, and U. Von-luxburg, Graph laplacians and their convergence on random neighborhood graphs, 2006.

Y. Ishikawa, R. Subramanya, and C. Faloutsos, Mindreader: query databases through multiple examples, Int'l Conf. on Very Large Data Bases (VLDB), 1998.

T. Kurita and T. Kato, Learning of personal visual impression for image database systems, Proceedings of 2nd International Conference on Document Analysis and Recognition (ICDAR '93), 1993.
DOI : 10.1109/ICDAR.1993.395676

S. Lafon, Y. Keller, and R. Coifman, Data Fusion and Multicue Data Matching by Diffusion Maps, IEEE transactions on PAMI, 2006.
DOI : 10.1109/TPAMI.2006.223

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.419.1814

S. Macarthur, C. Brodley, and C. Shyu, Relevance feedback decision trees in content-based image retrieval, 2000 Proceedings Workshop on Content-based Access of Image and Video Libraries, 2000.
DOI : 10.1109/IVL.2000.853842

C. Meilhac, M. Mitschke, and C. Nastar, Relevance feedback in Surfimage, Proceedings Fourth IEEE Workshop on Applications of Computer Vision. WACV'98 (Cat. No.98EX201), 1998.
DOI : 10.1109/ACV.1998.732899

H. Narayanan and M. Belkin, On the relation between low density separation, spectral clustering and graph cuts, NIPS, 2006.

R. Picard, T. Minka, and M. Szummer, Modeling user subjectivity in image libraries, Proceedings of 3rd IEEE International Conference on Image Processing, 1996.
DOI : 10.1109/ICIP.1996.561018

Y. Rui, T. Huang, and S. Mehrotra, Relevance feedback techniques in interactive content-based image retrieval. Storage and Retrieval for Image and Video Databases (SPIE), pp.25-36, 1998.

H. Sahbi, Kernel PCA for similarity invariant shape recognition, Neurocomputing, vol.70, issue.16-18, pp.3034-3045, 2006.
DOI : 10.1016/j.neucom.2006.06.007

G. Schohn and D. Cohn, Less is more: Active learning with support vector machines, Proceedings of the ICML, pp.839-846, 2000.

B. Scholkopf, R. Williamson, A. Smola, J. Taylor, and J. Platt, Support vector method for novelty detection, Adv. in Neural Information Processing Systems, 2000.

M. Seeger, Learning with labeled and unlabeled data, 2001.

A. Smeulders, M. Worring, S. Santini, A. Gupta, and R. Jain, Content-based image retrieval at the end of the early years, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.22, issue.12, pp.1349-1380, 2000.
DOI : 10.1109/34.895972

D. Spielman and S. Teng, Spectral partioning works: planar graphs and finite element meshes, 37th Ann. Symp. on Found. of Comp. Science (FOCS), pp.96-105, 1996.
DOI : 10.1016/j.laa.2006.07.020

URL : http://doi.org/10.1016/j.laa.2006.07.020

K. Tieu and P. Viola, Boosting image retrieval, IEEE Conf. Computer Vision and Pattern Recognition, 2000.
DOI : 10.1109/cvpr.2000.855824

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.136.2419

S. Tong and E. Chang, Support vector machine active learning for image retrieval, Proceedings of the ninth ACM international conference on Multimedia , MULTIMEDIA '01, pp.107-118, 2001.
DOI : 10.1145/500141.500159

N. Vasconcelos and A. Lippman, Learning from user feedback in image retrieval, Neural Information Processing Systems MIT press, 2000.

U. Von-luxburg, M. Belkin, and O. Bousquet, Consistency of spectral clustering, The Annals of Statistics, vol.36, issue.2, 2007.
DOI : 10.1214/009053607000000640

Y. Zhao, Y. Zhao, and Z. Zhu, Relevance feedback based on query refining and feature database updating in cbir system, Signal Processing, Pattern Recognition, and Applications, 2006.

X. Zhou and T. Huang, Relevance feedback in image retrieval: A comprehensive review, IEEE CVPR Workshop on Content-based Access of Image and Video Libraries (CBAIVL), 2006.
DOI : 10.1007/s00530-002-0070-3