A new look at the statistical model identification. Automatic Control, IEEE Transactions on, vol.19, issue.6, pp.716-723, 1974. ,
Kernel change-point detection ,
Learning spectral clustering, Adv. NIPS, 2003. ,
Learning a mahalanobis metric from equivalence constraints, Journal of Machine Learning Research, vol.6, issue.1, p.937, 2006. ,
Learning to Segment, Proc. ECCV, 2004. ,
DOI : 10.1007/978-3-540-24672-5_25
Consistencies and rates of convergence of jump-penalized least squares estimators, The Annals of Statistics, vol.37, issue.1, pp.157-183 ,
DOI : 10.1214/07-AOS558
Learning Graph Matching, IEEE 11th International Conference on Computer Vision, pp.1-8, 2007. ,
DOI : 10.1109/tpami.2009.28
URL : http://arxiv.org/abs/0806.2890
Parametric Statistical Change Point Analysis, Birkhäuser, 2011. ,
Mean shift, mode seeking, and clustering, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.17, issue.8, pp.790-799, 1995. ,
DOI : 10.1109/34.400568
Discriminative cluster analysis, Proceedings of the 23rd international conference on Machine learning , ICML '06, 2006. ,
DOI : 10.1145/1143844.1143875
An online kernel change detection algorithm, IEEE Transactions on Signal Processing, vol.53, issue.8, pp.2961-2974, 2005. ,
DOI : 10.1109/TSP.2005.851098
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.59.1469
On feature combination for multiclass object classification, 2009 IEEE 12th International Conference on Computer Vision, 2009. ,
DOI : 10.1109/ICCV.2009.5459169
Neighbourhood components analysis, Adv. NIPS, 2004. ,
Minimum Spanning Trees and Single Linkage Cluster Analysis, Applied Statistics, vol.18, issue.1, pp.54-64, 1969. ,
DOI : 10.2307/2346439
Learning smoothing models of copy number profiles using breakpoint annotations, BMC Bioinformatics, vol.14, issue.1, 2012. ,
DOI : 10.1186/gb-2004-5-10-r80
URL : https://hal.archives-ouvertes.fr/hal-00663790
Comparing partitions, Journal of Classification, vol.78, issue.1, pp.193-218, 1985. ,
DOI : 10.1007/BF01908075
Metric and kernel learning using a linear transformation, J. Mach. Learn. Res, vol.13, pp.519-547, 2012. ,
Discriminative clustering for image co-segmentation, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010. ,
DOI : 10.1109/CVPR.2010.5539868
Using penalized contrasts for the change-point problem, Signal Processing, vol.85, issue.8, pp.1501-1510, 2005. ,
DOI : 10.1016/j.sigpro.2005.01.012
URL : https://hal.archives-ouvertes.fr/inria-00070662
Learning object representations for visual object class recognition, 2007. ,
Metric learning to rank, Proceedings of the 27th annual International Conference on Machine Learning (ICML, 2010. ,
On spectral clustering: Analysis and an algorithm, Adv. NIPS, 2002. ,
Objective Criteria for the Evaluation of Clustering Methods, Journal of the American Statistical Association, vol.15, issue.336, pp.846-850, 1971. ,
DOI : 10.1080/01621459.1963.10500845
Normalized cuts and image segmentation, IEEE Trans. PAMI, vol.22, pp.888-905, 1997. ,
Learning CRFs Using Graph Cuts, Proc. ECCV, 2008. ,
DOI : 10.1007/978-3-540-88688-4_43
Max-margin markov networks, Adv. NIPS, 2003. ,
Bundle methods for regularized risk minimization, Journal of Machine Learning research, 2009. ,
Support vector machine learning for interdependent and structured output spaces, Twenty-first international conference on Machine learning , ICML '04, 2005. ,
DOI : 10.1145/1015330.1015341
Distance metric learning for large margin nearest neighbor classification, Adv. NIPS, 2006. [31] M. Welling. Robust higher order statistics. Proc. Int. Workshop Artif. Intell ,
Distance metric learning with applications to clustering with side-information, Adv. NIPS, 2002. ,
The Concave-Convex Procedure, Neural Computation, vol.39, issue.4, pp.915-936, 2003. ,
DOI : 10.1162/08997660260028674