2012
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}
}
2011
Lee, J; Maggioni, Mauro
Multiscale Analysis of Time Series of Graphs Conference
Proc. SampTA, 2011.
BibTeX | Tags: random walks, spectral graph theory
@conference{LM:sampta11,
title = {Multiscale Analysis of Time Series of Graphs},
author = {J Lee and Mauro Maggioni},
year = {2011},
date = {2011-01-01},
booktitle = {Proc. SampTA},
keywords = {random walks, spectral graph theory},
pubstate = {published},
tppubtype = {conference}
}
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 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}
}
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}
}
Szlam, Arthur D; Maggioni, Mauro; Coifman, Ronald R
Regularization on Graphs with Function-adapted Diffusion Processes Journal Article
In: Jour. Mach. Learn. Res., no. 9, pp. 1711–1739, 2008, ((YALE/DCS/TR1365, Yale Univ, July 2006)).
Links | BibTeX | Tags: diffusion geometry, Machine learning, Manifold Learning, random walks, semisupervised learning, spectral graph theory
@article{SMC:GeneralFrameworkAdaptiveRegularization,
title = {Regularization on Graphs with Function-adapted Diffusion Processes},
author = {Arthur D Szlam and Mauro Maggioni and Ronald R Coifman},
url = {https://jmlr.csail.mit.edu/papers/volume9/szlam08a/szlam08a.pdf},
year = {2008},
date = {2008-08-01},
urldate = {2008-08-01},
journal = {Jour. Mach. Learn. Res.},
number = {9},
pages = {1711--1739},
note = {(YALE/DCS/TR1365, Yale Univ, July 2006)},
keywords = {diffusion geometry, Machine learning, Manifold Learning, random walks, semisupervised learning, spectral graph theory},
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}
}
Mahadevan, Sridhar; Maggioni, Mauro
Proto-value Functions: A Spectral Framework for Solving Markov Decision Processes Journal Article
In: JMLR, vol. 8, pp. 2169–2231, 2007.
BibTeX | Tags: diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, reinforcement learning, representation learning, spectral graph theory
@article{smmm:jmrl1,
title = {Proto-value Functions: A Spectral Framework for Solving Markov Decision Processes},
author = {Sridhar Mahadevan and Mauro Maggioni},
year = {2007},
date = {2007-01-01},
journal = {JMLR},
volume = {8},
pages = {2169--2231},
keywords = {diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, reinforcement learning, representation learning, spectral graph theory},
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; Lafon, Stephane; Maggioni, Mauro; Keller, Y; Szlam, A D; Warner, F J; Zucker, S W
Geometries of sensor outputs, inference, and information processing Proceedings Article
In: Athale, John Zolper; Eds. C Intelligent Integrated Microsystems; Ravindra A. (Ed.): Proc. SPIE, pp. 623209, 2006.
BibTeX | Tags: diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, spectral graph theory, stochastic systems
@inproceedings{CLMKSWZ:GeometrySensorOutputs,
title = {Geometries of sensor outputs, inference, and information processing},
author = {Ronald R Coifman and Stephane Lafon and Mauro Maggioni and Y Keller and A D Szlam and F J Warner and S W Zucker},
editor = {John Zolper; Eds. C Intelligent Integrated Microsystems; Ravindra A. Athale},
year = {2006},
date = {2006-05-01},
booktitle = {Proc. SPIE},
volume = {6232},
pages = {623209},
keywords = {diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, spectral graph theory, stochastic systems},
pubstate = {published},
tppubtype = {inproceedings}
}
Maggioni, Mauro; Mahadevan, Sridhar
Fast Direct Policy Evaluation using Multiscale Analysis of Markov Diffusion Processes Proceedings Article
In: ICML 2006, pp. 601–608, 2006.
BibTeX | Tags: diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, reinforcement learning, representation learning, spectral graph theory
@inproceedings{smmm:FastDirectMDP,
title = {Fast Direct Policy Evaluation using Multiscale Analysis of Markov Diffusion Processes},
author = {Mauro Maggioni and Sridhar Mahadevan},
year = {2006},
date = {2006-01-01},
booktitle = {ICML 2006},
pages = {601--608},
keywords = {diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, reinforcement learning, representation learning, spectral graph theory},
pubstate = {published},
tppubtype = {inproceedings}
}
Mahadevan, Sridhar; Ferguson, Kim; Osentoski, Sarah; Maggioni, Mauro
Simultaneous Learning of Representation and Control In Continuous Domains Proceedings Article
In: AAAI, AAAI Press, 2006.
BibTeX | Tags: diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, reinforcement learning, representation learning, spectral graph theory
@inproceedings{smkfsomm:SimLearningReprControlContinuous,
title = {Simultaneous Learning of Representation and Control In Continuous Domains},
author = {Sridhar Mahadevan and Kim Ferguson and Sarah Osentoski and Mauro Maggioni},
year = {2006},
date = {2006-01-01},
booktitle = {AAAI},
publisher = {AAAI Press},
keywords = {diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, reinforcement learning, representation learning, spectral graph theory},
pubstate = {published},
tppubtype = {inproceedings}
}
2005
Coifman, Ronald R; Maggioni, Mauro; Zucker, Steven W; Kevrekidis, Ioannis G
Geometric diffusions for the analysis of data from sensor networks Journal Article
In: Curr Opin Neurobiol, vol. 15, no. 5, pp. 576–84, 2005.
BibTeX | Tags: diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, spectral graph theory, stochastic systems
@article{CMZK:CONB,
title = {Geometric diffusions for the analysis of data from sensor networks},
author = {Ronald R Coifman and Mauro Maggioni and Steven W Zucker and Ioannis G Kevrekidis},
year = {2005},
date = {2005-10-01},
journal = {Curr Opin Neurobiol},
volume = {15},
number = {5},
pages = {576--84},
keywords = {diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, spectral graph theory, stochastic systems},
pubstate = {published},
tppubtype = {article}
}
Coifman, Ronald R; Lafon, Stephane; Lee, Ann B; Maggioni, Mauro; Nadler, B; Warner, Frederick; Zucker, Steven W
Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 102, no. 21, pp. 7426-7431, 2005.
BibTeX | Tags: diffusion geometry, Machine learning, Manifold Learning, random walks, spectral graph theory, stochastic systems
@article{DiffusionPNAS,
title = {Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps},
author = {Ronald R Coifman and Stephane Lafon and Ann 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 = {7426-7431},
keywords = {diffusion geometry, Machine learning, Manifold Learning, random walks, spectral graph theory, stochastic systems},
pubstate = {published},
tppubtype = {article}
}
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}
}
Mahadevan, Sridhar; Maggioni, Mauro
Value Function Approximation with Diffusion Wavelets and Laplacian Eigenfunctions Proceedings Article
In: University of Massachusetts, Department of Computer Science Technical Report TR-2005-38; Proc. NIPS 2005, 2005.
BibTeX | Tags: diffusion geometry, diffusion wavelets, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, reinforcement learning, representation learning, spectral graph theory
@inproceedings{smmm:ValueFunction,
title = {Value Function Approximation with Diffusion Wavelets and Laplacian Eigenfunctions},
author = {Sridhar Mahadevan and Mauro Maggioni},
year = {2005},
date = {2005-01-01},
booktitle = {University of Massachusetts, Department of Computer Science Technical Report TR-2005-38; Proc. NIPS 2005},
keywords = {diffusion geometry, diffusion wavelets, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, reinforcement learning, representation learning, spectral graph theory},
pubstate = {published},
tppubtype = {inproceedings}
}
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}
}
- 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.