Adaptive Geometric Multiscale Approximations for Intrinsically
Low-dimensional Data

v1v2 (latest)

Adaptive Geometric Multiscale Approximations for Intrinsically Low-dimensional Data

3 November 2016

ArXiv (abs)PDF HTML

Papers citing "Adaptive Geometric Multiscale Approximations for Intrinsically Low-dimensional Data"

9 / 9 papers shown

Title
Manifold learning in Wasserstein space Keaton Hamm Caroline Moosmüller Bernhard Schmitzer Matthew Thorpe 77 5 0 14 Nov 2023
Multiscale Dictionary Learning: Non-Asymptotic Bounds and Robustness Mauro Maggioni Stanislav Minsker Nate Strawn 80 8 0 23 Jan 2014
Sample Complexity of Dictionary Learning and other Matrix Factorizations Rémi Gribonval Rodolphe Jenatton Francis R. Bach M. Kleinsteuber Matthias Seibert 127 85 0 13 Dec 2013
Learning Manifolds with K-Means and K-Flats Guillermo D. Cañas T. Poggio Lorenzo Rosasco 108 49 0 05 Sep 2012
Generalized Principal Component Analysis (GPCA) René Vidal Yi-An Ma S. Shankar Sastry 97 1,159 0 17 Feb 2012
Randomized hybrid linear modeling by local best-fit flats Teng Zhang Arthur Szlam Yi Wang Gilad Lerman 112 47 0 05 May 2010
K-Dimensional Coding Schemes in Hilbert Spaces Augusto Maurer 96 108 0 03 Feb 2010
Online Learning for Matrix Factorization and Sparse Coding Julien Mairal Francis R. Bach Jean Ponce Guillermo Sapiro 147 2,615 0 01 Aug 2009
Foundations of a Multi-way Spectral Clustering Framework for Hybrid Linear Modeling Guangliang Chen Gilad Lerman 100 75 0 21 Oct 2008