2019
Liao, Wenjing; Maggioni, Mauro
Adaptive Geometric Multiscale Approximations for Intrinsically Low-dimensional Data Journal Article
In: Journal of machine learning Research, vol. 20, no. 98, pp. 1-63, 2019.
Links | BibTeX | Tags: geometric wavelets, Machine learning, multiscale analysis, statistics
@article{LiaoMaggioni:GMRA,
title = {Adaptive Geometric Multiscale Approximations for Intrinsically Low-dimensional Data},
author = {Wenjing Liao and Mauro Maggioni},
url = {http://jmlr.org/papers/v20/17-252.html},
year = {2019},
date = {2019-01-01},
journal = {Journal of machine learning Research},
volume = {20},
number = {98},
pages = {1-63},
keywords = {geometric wavelets, Machine learning, multiscale analysis, statistics},
pubstate = {published},
tppubtype = {article}
}
2017
Gerber, Sam; Maggioni, Mauro
Multiscale Strategies for Discrete Optimal Transport Journal Article
In: Journ. Mach. Learn. Res., no. 72, pp. 1–32, 2017.
Links | BibTeX | Tags: multiscale analysis, optimal transport, optimization
@article{GM:mop,
title = {Multiscale Strategies for Discrete Optimal Transport},
author = {Sam Gerber and Mauro Maggioni},
url = {https://jmlr.csail.mit.edu/papers/volume18/16-108/16-108.pdf},
year = {2017},
date = {2017-01-01},
journal = {Journ. Mach. Learn. Res.},
number = {72},
pages = {1--32},
keywords = {multiscale analysis, optimal transport, optimization},
pubstate = {published},
tppubtype = {article}
}
Little, Anna V; Maggioni, Mauro; Rosasco, Lorenzo
Multiscale geometric methods for data sets I: Multiscale SVD, noise and curvature Journal Article
In: Applied and Computational Harmonic Analysis, vol. 43, no. 3, pp. 504 – 567, 2017, (Submitted: 2012, MIT-CSAIL-TR-2012-029/CBCL-310).
BibTeX | Tags: geometric wavelets, Machine learning, Manifold Learning, multiscale analysis, statistics
@article{LMR:MGM1,
title = {Multiscale geometric methods for data sets I: Multiscale SVD, noise and curvature},
author = {Anna V Little and Mauro Maggioni and Lorenzo Rosasco},
year = {2017},
date = {2017-01-01},
journal = {Applied and Computational Harmonic Analysis},
volume = {43},
number = {3},
pages = {504 - 567},
note = {Submitted: 2012, MIT-CSAIL-TR-2012-029/CBCL-310},
keywords = {geometric wavelets, Machine learning, Manifold Learning, multiscale analysis, statistics},
pubstate = {published},
tppubtype = {article}
}
2013
Gerber, S; Maggioni, Mauro
Multiscale dictionaries, transforms, and learning in high-dimensions Proceedings Article
In: Proc. SPIE conference Optics and Photonics, 2013.
BibTeX | Tags: dictionary learning, imaging, Machine learning, multiscale analysis
@inproceedings{GM_MultiscaleDictionariesSPIE,
title = {Multiscale dictionaries, transforms, and learning in high-dimensions},
author = {S Gerber and Mauro Maggioni},
year = {2013},
date = {2013-01-01},
booktitle = {Proc. SPIE conference Optics and Photonics},
keywords = {dictionary learning, imaging, Machine learning, multiscale analysis},
pubstate = {published},
tppubtype = {inproceedings}
}
Iwen, Mark A; Maggioni, Mauro
Approximation of points on low-dimensional manifolds via random linear projections Journal Article
In: Inference and Information, vol. 2, no. 1, pp. 1–31, 2013, (arXiv:1204.3337v1, 2012).
BibTeX | Tags: Machine learning, Manifold Learning, multiscale analysis
@article{IM:GMRA_CS,
title = {Approximation of points on low-dimensional manifolds via random linear projections},
author = {Mark A Iwen and Mauro Maggioni},
year = {2013},
date = {2013-01-01},
journal = {Inference and Information},
volume = {2},
number = {1},
pages = {1--31},
note = {arXiv:1204.3337v1, 2012},
keywords = {Machine learning, Manifold Learning, multiscale analysis},
pubstate = {published},
tppubtype = {article}
}
2012
Bouvrie, Jake; Maggioni, Mauro
Geometric Multiscale Reduction for Autonomous and Controlled Nonlinear Systems Proceedings Article
In: IEEE Conference on Decision and Control (CDC), 2012.
BibTeX | Tags: control theory, geometric wavelets, Machine learning, multiscale analysis
@inproceedings{BM_GMReductionControlledSystems,
title = {Geometric Multiscale Reduction for Autonomous and Controlled Nonlinear Systems},
author = {Jake Bouvrie and Mauro Maggioni},
year = {2012},
date = {2012-01-01},
booktitle = {IEEE Conference on Decision and Control (CDC)},
keywords = {control theory, geometric wavelets, Machine learning, multiscale analysis},
pubstate = {published},
tppubtype = {inproceedings}
}
Bouvrie, Jake; Maggioni, Mauro
Multiscale Markov Decision Problems: Compression, Solution, and Transfer Learning Journal Article
In: 2012.
Links | BibTeX | Tags: Machine learning, multiscale analysis, reinforcement learning, representation learning, spectral graph theory, transfer learning
@article{BM:MMDPs,
title = {Multiscale Markov Decision Problems: Compression, Solution, and Transfer Learning},
author = {Jake Bouvrie and Mauro Maggioni},
url = {http://arxiv.org/abs/1212.1143},
year = {2012},
date = {2012-01-01},
keywords = {Machine learning, multiscale analysis, reinforcement learning, representation learning, spectral graph theory, transfer learning},
pubstate = {published},
tppubtype = {article}
}
Allard, William K; Chen, Guangliang; Maggioni, Mauro
Multi-scale geometric methods for data sets II: Geometric Multi-Resolution Analysis Journal Article
In: Applied and Computational Harmonic Analysis, vol. 32, no. 3, pp. 435–462, 2012.
BibTeX | Tags: geometric wavelets, Machine learning, Manifold Learning, multiscale analysis, statistics
@article{CM:MGM2,
title = {Multi-scale geometric methods for data sets II: Geometric Multi-Resolution Analysis},
author = {William K Allard and Guangliang Chen and Mauro Maggioni},
year = {2012},
date = {2012-01-01},
journal = {Applied and Computational Harmonic Analysis},
volume = {32},
number = {3},
pages = {435--462},
keywords = {geometric wavelets, Machine learning, Manifold Learning, multiscale analysis, statistics},
pubstate = {published},
tppubtype = {article}
}
2011
Chen, Guangliang; Little, Anna V; Maggioni, Mauro
Multi-Resolution Geometric Analysis for data in high dimensions Journal Article
In: Proc. FFT 2011, 2011.
BibTeX | Tags: geometric wavelets, Machine learning, Manifold Learning, multiscale analysis
@article{FFT2011,
title = {Multi-Resolution Geometric Analysis for data in high dimensions},
author = {Guangliang Chen and Anna V Little and Mauro Maggioni},
year = {2011},
date = {2011-08-01},
journal = {Proc. FFT 2011},
keywords = {geometric wavelets, Machine learning, Manifold Learning, multiscale analysis},
pubstate = {published},
tppubtype = {article}
}
Maggioni, Mauro
Multiscale Geometric Dictionaries for Point-Cloud Data, Presented at SPARS 11, http://www.math.duke.edu/~mauro/research.html#Talks Journal Article
In: 2011, (Presented at SPARS 11).
Links | BibTeX | Tags: dictionary learning, geometric wavelets, Machine learning, Manifold Learning, multiscale analysis
@article{MM:Spars11talk,
title = {Multiscale Geometric Dictionaries for Point-Cloud Data, Presented at SPARS 11, http://www.math.duke.edu/~mauro/research.html#Talks},
author = {Mauro Maggioni},
url = {http://www.math.duke.edu/~mauro/research.html#Talks},
year = {2011},
date = {2011-06-01},
note = {Presented at SPARS 11},
keywords = {dictionary learning, geometric wavelets, Machine learning, Manifold Learning, multiscale analysis},
pubstate = {published},
tppubtype = {article}
}
Chen, Guangliang; Maggioni, Mauro
Multiscale Geometric Dictionaries for Point-Cloud Data Proceedings Article
In: Proc. SampTA, 2011.
BibTeX | Tags: dictionary learning, geometric wavelets, Machine learning, Manifold Learning, multiscale analysis
@inproceedings{CM:SamptaGW,
title = {Multiscale Geometric Dictionaries for Point-Cloud Data},
author = {Guangliang Chen and Mauro Maggioni},
year = {2011},
date = {2011-01-01},
booktitle = {Proc. SampTA},
keywords = {dictionary learning, geometric wavelets, Machine learning, Manifold Learning, multiscale analysis},
pubstate = {published},
tppubtype = {inproceedings}
}
Chen, Guangliang; Maggioni, Mauro
Multiscale Geometric and Spectral Analysis of Plane Arrangements Proceedings Article
In: Conference on Computer Vision and Pattern Recognition, 2011.
BibTeX | Tags: Machine learning, Manifold Learning, multiscale analysis
@inproceedings{CM:CVPR2011,
title = {Multiscale Geometric and Spectral Analysis of Plane Arrangements},
author = {Guangliang Chen and Mauro Maggioni},
year = {2011},
date = {2011-01-01},
booktitle = {Conference on Computer Vision and Pattern Recognition},
keywords = {Machine learning, Manifold Learning, multiscale analysis},
pubstate = {published},
tppubtype = {inproceedings}
}
2010
Jones, Peter W; Maggioni, Mauro; Schul, Raanan
Universal local manifold parametrizations via heat kernels and eigenfunctions of the Laplacian Journal Article
In: Ann. Acad. Scient. Fen., vol. 35, pp. 1–44, 2010, (http://arxiv.org/abs/0709.1975).
BibTeX | Tags: diffusion geometry, heat kernels, Laplacian eigenfunctions, Manifold Learning, multiscale analysis, random walks, spectral graph theory
@article{jms:UniformizationEigenfunctions2,
title = {Universal local manifold parametrizations via heat kernels and eigenfunctions of the Laplacian},
author = {Peter W Jones and Mauro Maggioni and Raanan Schul},
year = {2010},
date = {2010-01-01},
journal = {Ann. Acad. Scient. Fen.},
volume = {35},
pages = {1--44},
note = {http://arxiv.org/abs/0709.1975},
keywords = {diffusion geometry, heat kernels, Laplacian eigenfunctions, Manifold Learning, multiscale analysis, random walks, spectral graph theory},
pubstate = {published},
tppubtype = {article}
}
Chen, Guangliang; Maggioni, Mauro
Multiscale Geometric Methods for Data Sets III: multiple planes Journal Article
In: in preparation, 2010.
BibTeX | Tags: Machine learning, Manifold Learning, multiscale analysis, statistics
@article{CM:MGM3,
title = {Multiscale Geometric Methods for Data Sets III: multiple planes},
author = {Guangliang Chen and Mauro Maggioni},
year = {2010},
date = {2010-01-01},
journal = {in preparation},
keywords = {Machine learning, Manifold Learning, multiscale analysis, statistics},
pubstate = {published},
tppubtype = {article}
}
Chen, Guangliang; Maggioni, Mauro
Multiscale Geometric Wavelets for the Analysis of Point Clouds Journal Article
In: Proc. CISS 2010, 2010.
BibTeX | Tags: geometric wavelets, Machine learning, Manifold Learning, multiscale analysis, spectral graph theory
@article{CM:geometricwaveletsciss,
title = {Multiscale Geometric Wavelets for the Analysis of Point Clouds},
author = {Guangliang Chen and Mauro Maggioni},
year = {2010},
date = {2010-01-01},
journal = {Proc. CISS 2010},
keywords = {geometric wavelets, Machine learning, Manifold Learning, multiscale analysis, spectral graph theory},
pubstate = {published},
tppubtype = {article}
}
2009
Little, Anna V; Jung, Y -M; Maggioni, Mauro
Multiscale Estimation of Intrinsic Dimensionality of Data Sets Proceedings Article
In: Proc. A.A.A.I., 2009.
BibTeX | Tags: Machine learning, Manifold Learning, multiscale analysis, statistics
@inproceedings{MM:MultiscaleDimensionalityEstimationAAAI,
title = {Multiscale Estimation of Intrinsic Dimensionality of Data Sets},
author = {Anna V Little and Y -M Jung and Mauro Maggioni},
year = {2009},
date = {2009-01-01},
booktitle = {Proc. A.A.A.I.},
keywords = {Machine learning, Manifold Learning, multiscale analysis, statistics},
pubstate = {published},
tppubtype = {inproceedings}
}
Little, Anna V; Lee, J; Jung, Y -M; Maggioni, Mauro
Estimation of intrinsic dimensionality of samples from noisy low-dimensional manifolds in high dimensions with multiscale $SVD$ Proceedings Article
In: Proc. S.S.P., 2009.
BibTeX | Tags: Machine learning, Manifold Learning, multiscale analysis, statistics
@inproceedings{MM:MultiscaleDimensionalityEstimationSSP,
title = {Estimation of intrinsic dimensionality of samples from noisy low-dimensional manifolds in high dimensions with multiscale $SVD$},
author = {Anna V Little and J Lee and Y -M Jung and Mauro Maggioni},
year = {2009},
date = {2009-01-01},
booktitle = {Proc. S.S.P.},
keywords = {Machine learning, Manifold Learning, multiscale analysis, statistics},
pubstate = {published},
tppubtype = {inproceedings}
}
2008
Coifman, Ronald R; Maggioni, Mauro
Geometry Analysis and Signal Processing on Digital Data, Emergent Structures, and Knowledge Building Miscellaneous
SIAM News, 2008.
BibTeX | Tags: diffusion geometry, heat kernels, Laplacian eigenfunctions, Manifold Learning, multiscale analysis, random walks, spectral graph theory
@misc{CM:SiamNews,
title = {Geometry Analysis and Signal Processing on Digital Data, Emergent Structures, and Knowledge Building},
author = {Ronald R Coifman and Mauro Maggioni},
year = {2008},
date = {2008-11-01},
howpublished = {SIAM News},
keywords = {diffusion geometry, heat kernels, Laplacian eigenfunctions, Manifold Learning, multiscale analysis, random walks, spectral graph theory},
pubstate = {published},
tppubtype = {misc}
}
Maggioni, Mauro; Mhaskar, Hrushikesh
Diffusion polynomial frames on metric measure spaces Journal Article
In: ACHA, vol. 3, pp. 329–353, 2008.
BibTeX | Tags: approximation theory, diffusion geometry, heat kernels, Laplacian eigenfunctions, multiscale analysis
@article{MM:DiffusionPolynomialFrames,
title = {Diffusion polynomial frames on metric measure spaces},
author = {Mauro Maggioni and Hrushikesh Mhaskar},
year = {2008},
date = {2008-05-01},
journal = {ACHA},
volume = {3},
pages = {329--353},
keywords = {approximation theory, diffusion geometry, heat kernels, Laplacian eigenfunctions, multiscale analysis},
pubstate = {published},
tppubtype = {article}
}
Jones, Peter W; Maggioni, Mauro; Schul, Raanan
Manifold parametrizations by eigenfunctions of the Laplacian and heat kernels Journal Article
In: Proc. Nat. Acad. Sci., vol. 105, no. 6, pp. 1803–1808, 2008.
BibTeX | Tags: diffusion geometry, heat kernels, Laplacian eigenfunctions, Manifold Learning, multiscale analysis, random walks, spectral graph theory
@article{jms:UniformizationEigenfunctions,
title = {Manifold parametrizations by eigenfunctions of the Laplacian and heat kernels},
author = {Peter W Jones and Mauro Maggioni and Raanan Schul},
year = {2008},
date = {2008-02-01},
journal = {Proc. Nat. Acad. Sci.},
volume = {105},
number = {6},
pages = {1803--1808},
keywords = {diffusion geometry, heat kernels, Laplacian eigenfunctions, Manifold Learning, multiscale analysis, random walks, spectral graph theory},
pubstate = {published},
tppubtype = {article}
}
2007
Coifman, Ronald R; Maggioni, Mauro
Multiscale Data Analysis with Diffusion Wavelets Journal Article
In: Proc. SIAM Bioinf. Workshop, Minneapolis, 2007.
BibTeX | Tags: diffusion geometry, diffusion wavelets, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory, stochastic systems
@article{CM:MsDataDiffWavelets,
title = {Multiscale Data Analysis with Diffusion Wavelets},
author = {Ronald R Coifman and Mauro Maggioni},
year = {2007},
date = {2007-04-01},
journal = {Proc. SIAM Bioinf. Workshop, Minneapolis},
keywords = {diffusion geometry, diffusion wavelets, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory, stochastic systems},
pubstate = {published},
tppubtype = {article}
}
2006
Coifman, Ronald R; Maggioni, Mauro
Diffusion Wavelets Journal Article
In: Appl. Comp. Harm. Anal., vol. 21, no. 1, pp. 53–94, 2006, ((Tech. Rep. YALE/DCS/TR-1303, Yale Univ., Sep. 2004)).
BibTeX | Tags: diffusion geometry, diffusion wavelets, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory, stochastic systems
@article{CMDiffusionWavelets,
title = {Diffusion Wavelets},
author = {Ronald R Coifman and Mauro Maggioni},
year = {2006},
date = {2006-07-01},
journal = {Appl. Comp. Harm. Anal.},
volume = {21},
number = {1},
pages = {53--94},
note = {(Tech. Rep. YALE/DCS/TR-1303, Yale Univ., Sep. 2004)},
keywords = {diffusion geometry, diffusion wavelets, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory, stochastic systems},
pubstate = {published},
tppubtype = {article}
}
Bremer, James Jr. C; Coifman, Ronald R; Maggioni, Mauro; Szlam, Arthur D
Diffusion Wavelet Packets Journal Article
In: Appl. Comp. Harm. Anal., vol. 21, no. 1, pp. 95–112, 2006, ((Tech. Rep. YALE/DCS/TR-1304, 2004)).
BibTeX | Tags: diffusion geometry, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory, stochastic systems
@article{DiffusionWaveletPackets,
title = {Diffusion Wavelet Packets},
author = {James Jr. C Bremer and Ronald R Coifman and Mauro Maggioni and Arthur D Szlam},
year = {2006},
date = {2006-07-01},
journal = {Appl. Comp. Harm. Anal.},
volume = {21},
number = {1},
pages = {95--112},
note = {(Tech. Rep. YALE/DCS/TR-1304, 2004)},
keywords = {diffusion geometry, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory, stochastic systems},
pubstate = {published},
tppubtype = {article}
}
Coifman, Ronald R; Maggioni, Mauro
Multiscale Analysis of Document Corpora Unpublished
2006, (Technical Report).
BibTeX | Tags: Machine learning, Manifold Learning, multiscale analysis, Unsupervised Learning
@unpublished{CM:MultiscaleAnalysisOfDocumentCorpora,
title = {Multiscale Analysis of Document Corpora},
author = {Ronald R Coifman and Mauro Maggioni},
year = {2006},
date = {2006-01-01},
note = {Technical Report},
keywords = {Machine learning, Manifold Learning, multiscale analysis, Unsupervised Learning},
pubstate = {published},
tppubtype = {unpublished}
}
2005
Coifman, Ronald R; Lafon, S; Lee, A B; Maggioni, Mauro; Nadler, B; Warner, Frederick; Zucker, Steven W
Geometric diffusions as a tool for harmonic analysis and structure definition of data: Multiscale methods Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 102, no. 21, pp. 7432–7438, 2005.
BibTeX | Tags: diffusion geometry, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory, stochastic systems
@article{DiffusionPNAS2,
title = {Geometric diffusions as a tool for harmonic analysis and structure definition of data: Multiscale methods},
author = {Ronald R Coifman and S Lafon and A B Lee and Mauro Maggioni and B Nadler and Frederick Warner and Steven W Zucker},
year = {2005},
date = {2005-01-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {102},
number = {21},
pages = {7432--7438},
keywords = {diffusion geometry, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory, stochastic systems},
pubstate = {published},
tppubtype = {article}
}
Maggioni, Mauro; Bremer, James Jr. C; Coifman, Ronald R; Szlam, Arthur D
Biorthogonal diffusion wavelets for multiscale representations on manifolds and graphs Conference
vol. 5914, no. 1, SPIE, San Diego, CA, USA, 2005.
Links | BibTeX | Tags: diffusion geometry, diffusion wavelets, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory
@conference{MBCS:BiorthogonalDiffusionWavelets,
title = {Biorthogonal diffusion wavelets for multiscale representations on manifolds and graphs},
author = {Mauro Maggioni and James Jr. C Bremer and Ronald R Coifman and Arthur D Szlam},
editor = {Manos Papadakis and Andrew F Laine and Michael A Unser},
url = {http://link.aip.org/link/?PSI/5914/59141M/1},
year = {2005},
date = {2005-01-01},
journal = {Wavelets XI},
volume = {5914},
number = {1},
pages = {59141M},
publisher = {SPIE},
address = {San Diego, CA, USA},
keywords = {diffusion geometry, diffusion wavelets, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory},
pubstate = {published},
tppubtype = {conference}
}
Szlam, Arthur D; Maggioni, Mauro; Coifman, Ronald R; Bremer, James Jr. C
Diffusion-driven multiscale analysis on manifolds and graphs: top-down and bottom-up constructions Conference
vol. 5914-1, SPIE, San Diego, CA, USA, 2005.
Links | BibTeX | Tags: diffusion geometry, diffusion wavelets, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory
@conference{MSCB:MultiscaleManifoldMethods,
title = {Diffusion-driven multiscale analysis on manifolds and graphs: top-down and bottom-up constructions},
author = {Arthur D Szlam and Mauro Maggioni and Ronald R Coifman and James Jr. C Bremer},
editor = {Manos Papadakis and Andrew F Laine and Michael A Unser},
url = {http://link.aip.org/link/?PSI/5914/59141D/1},
year = {2005},
date = {2005-01-01},
journal = {Wavelets XI},
volume = {5914-1},
pages = {59141D},
publisher = {SPIE},
address = {San Diego, CA, USA},
keywords = {diffusion geometry, diffusion wavelets, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory},
pubstate = {published},
tppubtype = {conference}
}
2004
Coifman, Ronald R; Maggioni, Mauro
Multiresolution Analysis associated to diffusion semigroups: construction and fast algorithms Technical Report
Dept. Comp. Sci., Yale University no. YALE/DCS/TR-1289, 2004.
BibTeX | Tags: diffusion geometry, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory, stochastic systems
@techreport{CMTech,
title = {Multiresolution Analysis associated to diffusion semigroups: construction and fast algorithms},
author = {Ronald R Coifman and Mauro Maggioni},
year = {2004},
date = {2004-05-01},
number = {YALE/DCS/TR-1289},
institution = {Dept. Comp. Sci., Yale University},
keywords = {diffusion geometry, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory, stochastic systems},
pubstate = {published},
tppubtype = {techreport}
}
Ferrari, S; Maggioni, Mauro; Borghese, N A
Multi-Scale Approximation with Hierarchical Radial Basis Functions Networks, Journal Article
In: IEEE Trans. on Neural Networks, vol. 15, no. 1, pp. 178–188, 2004.
BibTeX | Tags: approximation theory, multiscale analysis, radial basis functions
@article{MRA_HRBF2004,
title = {Multi-Scale Approximation with Hierarchical Radial Basis Functions Networks,},
author = {S Ferrari and Mauro Maggioni and N A Borghese},
year = {2004},
date = {2004-01-01},
journal = {IEEE Trans. on Neural Networks},
volume = {15},
number = {1},
pages = {178--188},
keywords = {approximation theory, multiscale analysis, radial basis functions},
pubstate = {published},
tppubtype = {article}
}
- Lectures at Summer School at Peking University, July 2017.
- PCMI Lectures, Summer 2016: Lecture 1, Lecture 2, Problems/discussion points
- Google Scholar
- Papers on the ArXiv
- Papers on MathsciNet
- Tutorials on diffusion geometry and multiscale analysis on graphs at the MRA Internet Program at IPAM: Part I and Part II.
- Diffusion Geometries, Diffusion Wavelets and Harmonic Analysis of large data sets, IPAM, Multiscale Geometric Analysis Program, Fall 2004.
- Diffusion Geometries, global and multiscale, IPAM, 2005.