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Planar disk graph proof citesee
Planar disk graph proof citesee




planar disk graph proof citesee

In: 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. Springer, New York (2008)īronstein, M.M., Kokkinos, I.: Scale-invariant heat kernel signatures for non-rigid shape recognition.

planar disk graph proof citesee

Springer, Heidelberg (2003)īronstein, A.M., Bronstein, M.M., Kimmel, R.: Numerical Geometry of Non-Rigid Shapes. īoyer, D.M., Puente, J., Gladman, J.T., Glynn, C., Mukherjee, S., Yapuncich, G.S., Daubechies, I.: A new fully automated approach for aligning and comparing shapes. Clair, E., Puente, J., Patel, B.A., Funkhouser, T., Jernvall, J., Daubechies, I.: Algorithms to automatically quantify the geometric similarity of anatomical surfaces. Inference 3(1), 1–39 (2014)īoyer, D.M.: Relief index of second mandibular molars is a correlate of diet among prosimian primates and other euarchontan mammals. Springer, New York (1982)īoumal, N., Singer, A., Absil, P.A., Blondel, V.D.: Cramér-Rao bounds for synchronization of rotations. Springer, Heidelberg (2008)īolibrukh, A.A.: The Riemann-Hilbert problem. 56(1–3), 209–239 (2004)īlitzstein, J., Diaconis, P.: A sequential importance sampling algorithm for generating random graphs with prescribed degrees. īelkin, M., Niyogi, P.: Semi-supervised learning on Riemannian manifolds. 453, 49–86 (2008)īelkin, M., Niyogi, P.: Laplacian eigenmaps for dimensionality reduction and data representation. īandeira, A.S., Singer, A., Spielman, D.A.: A cheeger inequality for the graph connection Laplacian. arXiv:1505.03840īandeira, A.S., Kennedy, C., Singer, A.: Approximating the Little Grothendieck Problem over the Orthogonal and Unitary Groups.

planar disk graph proof citesee

ACM, New York (2014)īandeira, A.S., Chen, Y., Singer, A.: Non-unique Games over Compact Groups and Orientation Estimation in Cryo-EM (2015). In: Proceedings of the 5th Conference on Innovations in Theoretical Computer Science, pp. īandeira, A.S., Charikar, M., Singer, A., Zhu, A.: Multireference alignment using semidefinite programming. In: Proceedings of the 35th International Conference on Machine Learning, vol. īajaj, C., Gao, T., He, Z., Huang, Q., Liang, Z.: SMAC: simultaneous mapping and clustering using spectral decompositions. In: 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), pp. 308(1505), 523–615 (1983)Īubry, M., Schlickewei, U., Cremers, D.: The wave kernel signature: a quantum mechanical approach to shape analysis. 15, 1–155 (2006)Ītiyah, M.F., Bott, R.: The Yang–Mills equations over Riemann surfaces. Vieweg, Braunschweig (1994)Īrnold, D.N., Falk, R.S., Winther, R.: Finite element exterior calculus, homological techniques, and applications. Īnosov, D.V., Bolibruch, A.A.: The Riemann–Hilbert problem. 24(1), 78–100 (1995)Īngenent, S., Haker, S., Tannenbaum, A., Kikinis, R.: On the Laplace-Beltrami operator and brain surface flattening. Īlon, N., Karp, R.M., Peleg, D., West, D.: A graph-theoretic game and its application to the k-server problem. (TOG) 34(4), 72 (2015)Īl-Aifari, R., Daubechies, I., Lipman, Y.: Continuous procrustes distance between two surfaces. We demonstrate the efficacy of this algorithm on simulated and real datasets.Īigerman, N., Poranne, R., Lipman, Y.: Seamless surface mappings. Motivated by these geometric intuitions, we propose to study the problem of learning group actions-partitioning a collection of objects based on the local synchronizability of pairwise correspondence relations-and provide a heuristic synchronization-based algorithm for solving this type of problems. We then develop a twisted Hodge theory on flat vector bundles associated with these flat principal G-bundles, and provide a geometric realization of the graph connection Laplacian as the lowest-degree Hodge Laplacian in the twisted de Rham–Hodge cochain complex. We identify each synchronization problem in topological group G on connected graph \(\Gamma \) with a flat principal G-bundle over \(\Gamma \), thus establishing a classification result for synchronization problems using the representation variety of the fundamental group of \(\Gamma \) into G. We develop a geometric framework, based on the classical theory of fibre bundles, to characterize the cohomological nature of a large class of synchronization-type problems in the context of graph inference and combinatorial optimization.






Planar disk graph proof citesee