Gilad Lerman
Gilad Lerman
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Spectral curvature clustering (SCC)
G Chen, G Lerman
International Journal of Computer Vision 81 (3), 317-330, 2009
Randomized hybrid linear modeling by local best-fit flats
T Zhang, A Szlam, Y Wang, G Lerman
Proceedings of the IEEE Computer Society Conference on Computer Vision and …, 2010
Hybrid linear modeling via local best-fit flats
T Zhang, A Szlam, Y Wang, G Lerman
International journal of computer vision 100 (3), 217-240, 2012
Median K-flats for hybrid linear modeling with many outliers
T Zhang, A Szlam, G Lerman
Computer Vision Workshops (ICCV Workshops), 2009 IEEE 12th International …, 2009
Robust computation of linear models by convex relaxation
G Lerman, M McCoy, JA Tropp, T Zhang
Foundations of Computational Mathematics 15 (2), 363-410, 2015
A novel M-estimator for robust PCA
T Zhang, G Lerman
The Journal of Machine Learning Research 15 (1), 749-808, 2014
Robust recovery of multiple subspaces by geometric lp minimization
G Lerman, T Zhang
The Annals of Statistics 39 (5), 2686-2715, 2011
Spectral clustering based on local linear approximations
E Arias-Castro, G Chen, G Lerman
Electronic Journal of Statistics 5, 1537-1587, 2011
Foundations of a multi-way spectral clustering framework for hybrid linear modeling
G Chen, G Lerman
Foundations of Computational Mathematics 9 (5), 517-558, 2009
Spectral clustering based on local PCA
E Arias-Castro, G Lerman, T Zhang
Journal of Machine Learning Research 18 (9), 1-57, 2017
Quantifying curvelike structures of measures by using L2 Jones quantities
G Lerman
Communications on Pure and Applied Mathematics: A Journal Issued by the …, 2003
Defining functional distance using manifold embeddings of gene ontology annotations
G Lerman, BE Shakhnovich
Proceedings of the National Academy of Sciences 104 (27), 11334-11339, 2007
Robust locally linear analysis with applications to image denoising and blind inpainting
Y Wang, A Szlam, G Lerman
SIAM Journal on Imaging Sciences 6 (1), 526-562, 2013
Emerging challenges in computational topology
M Bern, D Eppstein, PK Agarwal, N Amenta, P Chew, T Dey, DP Dobkin, ...
arXiv preprint cs/9909001, 1999
High-Dimensional Menger-Type Curvatures—Part II: d-Separation and a Menagerie of Curvatures
G Lerman, JT Whitehouse
Constructive Approximation 30 (3), 325, 2009
Robust stochastic principal component analysis
J Goes, T Zhang, R Arora, G Lerman
Artificial Intelligence and Statistics, 266-274, 2014
High-dimensional Menger-type curvatures. Part I: Geometric multipoles and multiscale inequalities
G Lerman, JT Whitehouse
Revista Matemática Iberoamericana 27 (2), 493-555, 2011
Kernel spectral curvature clustering (KSCC)
G Chen, S Atev, G Lerman
2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV …, 2009
On d-dimensional d-semimetrics and simplex-type inequalities for high-dimensional sine functions
G Lerman, JT Whitehouse
Journal of Approximation Theory 156 (1), 52-81, 2009
An overview of robust subspace recovery
G Lerman, T Maunu
Proceedings of the IEEE 106 (8), 1380-1410, 2018
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