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**Applied harmonic analysis and sparse approximation. Abstracts from the workshop held June 10–16, 2012.**
*(English)*
Zbl 1349.00127

Summary: Applied harmonic analysis and sparse approximation are highly active research areas with a lot of recent exciting developments. Their methods have become crucial for a wide range of applications in technology and science, such as signal and image processing. Understanding of the underlying mathematics has grown vastly. Interestingly, there are a lot of connections to other fields, such as convex optimization, probability theory and Banach space geometry. Yet, many problems in these areas remain unsolved or even unattacked. The workshop intended to bring together world leading experts in these areas, to report on recent developments, and to foster new developments and collaborations.

### MSC:

00B05 | Collections of abstracts of lectures |

00B25 | Proceedings of conferences of miscellaneous specific interest |

42-06 | Proceedings, conferences, collections, etc. pertaining to harmonic analysis on Euclidean spaces |

65-06 | Proceedings, conferences, collections, etc. pertaining to numerical analysis |

65Txx | Numerical methods in Fourier analysis |

94Axx | Communication, information |

65K05 | Numerical mathematical programming methods |

15B52 | Random matrices (algebraic aspects) |

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\textit{I. Daubechies} (ed.) et al., Oberwolfach Rep. 9, No. 2, 1759--1843 (2012; Zbl 1349.00127)

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### References:

[1] | A. Aldroubi and A. Sekmen, Reduced Row Echelon Form and Non-Linear Approximation for Subspace Segmentation and High-Dimensional Data Clustering, preprint (2012). · Zbl 1314.94011 |

[2] | A. Aldroubi and A. Sekmen, Nearness to Local Subspace Algorithm for Subspace and Motion Segmentation, (2011), preprint. · Zbl 1314.94011 |

[3] | A. Aldroubi I. Krishtal, R. Tessera, and H. Wang, Principle shift-invariant spaces with extra invariance nearest to observed data, Collectanea Mathematica, (2011). · Zbl 1278.46026 |

[4] | A. Aldroubi and R. Tessera, On the existence of optimal unions of subspaces for data modeling and clustering, Foundation of Computational Mathematics 11 (3) (2011), 363– 379. · Zbl 1218.68091 |

[5] | A. Aldroubi, C. Cabrelli, and U. Molter, Optimal non-linear models for sparsity and sampling, J. of Fourier Anal. and Applications 14 (5) (2009), 793–812. · Zbl 1202.42051 |

[6] | A. Aldroubi, C. Cabrelli, D. Hardin, and U. Molter, Optimal shift-invariant spaces and their Parseval frame generators, Appl. Comput. Harmon. Anal. (2007), 273–283. · Zbl 1133.42042 |

[7] | E. Elhamifar, R. Vidal, Sparse subspace clustering, in: IEEE Conference on Computer Vision and Pattern Recognition, pp. 2790–2797. |

[8] | G. Lerman, T. Zhang, Robust recovery of multiple subspaces by geometric lp minimization 39(2011) 2686–2715. · Zbl 1232.62097 |

[9] | M. Soltanolkotabi and E. J. Cand‘es, A geometric analysis of subspace clustering with outliers preprint (2011). |

[10] | R. Vidal, A tutorial on subspace clustering, IEEE Signal Processing Magazine (2010). |

[11] | R. Vidal, Y. Ma, and S. Sastry, Generalized principal component analysis (GPCA), IEEE Transactions on Pattern Analysis and Machine Intelligence, 27 (2005) 1945–1959. |

[12] | T. Zhang, A. Szlam, Y. Wang, G. Lerman. Hybrid Linear Modeling via Local Best-fit Flats. Arxiv preprint, (2010). Applied Harmonic Analysis and Sparse Approximation1769 |

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