A tutorial on spectral clustering, Statistics and Computing, vol.21, issue.1, pp.395-416, 2007. ,
DOI : 10.1007/s11222-007-9033-z
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
Spectral partitioning works: Planar graphs and finite element meshes, Linear Algebra and its Applications, vol.421, issue.2-3, pp.284-305, 2007. ,
DOI : 10.1016/j.laa.2006.07.020
Articulated shape matching using Laplacian eigenfunctions and unsupervised point registration, 2008 IEEE Conference on Computer Vision and Pattern Recognition, p.CVPR, 2008. ,
DOI : 10.1109/CVPR.2008.4587538
URL : https://hal.archives-ouvertes.fr/inria-00590251
Rigid and Articulated Point Registration with Expectation Conditional Maximization, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.33, issue.3, 2010. ,
DOI : 10.1109/TPAMI.2010.94
URL : https://hal.archives-ouvertes.fr/inria-00435772
Shrec 2010: Robust correspondence benchmark, Eurographics Workshop on 3D Object Retrieval, 2010. ,
A Gromov-Hausdorff framework with diffusion geometry for topologically robust non-rigid shape alignment, pp.266-286, 2010. ,
Global Intrinsic Symmetries of Shapes, Computer Graphics Forum, vol.27, issue.2, pp.1341-1348, 2008. ,
DOI : 10.1111/j.1467-8659.2008.01273.x
A benchmark for 3d mesh segmentation, In: ACM Transactions on Graphics, 2009. ,
Hierarchical Shape Segmentation and Registration via??Topological Features of Laplace-Beltrami Eigenfunctions, International Journal of Computer Vision, vol.21, issue.6, pp.287-308, 2010. ,
DOI : 10.1007/s11263-009-0278-1
Mesh Segmentation via Spectral Embedding and Contour Analysis, Computer Graphics Forum, vol.26, issue.7, pp.385-394, 2007. ,
DOI : 10.1111/1467-8659.00581
Partially labeled classification with Markov random walks, p.NIPS, 2002. ,
Diffusion maps, Applied and Computational Harmonic Analysis, vol.21, issue.1, pp.5-30, 2006. ,
DOI : 10.1016/j.acha.2006.04.006
Clustering and Embedding Using Commute Times, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.29, issue.11, pp.1873-1890, 2007. ,
DOI : 10.1109/TPAMI.2007.1103
Semi-Supervised Learning on Riemannian Manifolds, Machine Learning, vol.56, issue.1-3, 2004. ,
DOI : 10.1023/B:MACH.0000033120.25363.1e
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.78.2757
Constrained k-means clustering with background knowledge, p.ICML, 2001. ,
Distance metric learning with application to clustering with side-information, p.NIPS, 2002. ,
Integrating constraints and metric learning in semisupervised clustering, p.ICML, 2004. ,
Constrained clustering by spectral kernel learning, p.ICCV, 2009. ,
Semi-supervised graph clustering, Proceedings of the 22nd international conference on Machine learning , ICML '05, pp.1-22, 2009. ,
DOI : 10.1145/1102351.1102409
Spectral learning, p.IJCAI, 2003. ,
Segmentation given partial grouping constraints, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, issue.2, pp.173-183, 2004. ,
DOI : 10.1109/TPAMI.2004.1262179
Random-Walk Computation of Similarities between Nodes of a Graph with Application to Collaborative Recommendation, IEEE Transactions on Knowledge and Data Engineering, vol.19, issue.3, pp.355-369, 2007. ,
DOI : 10.1109/TKDE.2007.46
Introduction to Probability, 1998. ,