2023
An, Qingci; Kevrekidis, Yannis; Lu, Fei; Maggioni, Mauro
Unsupervised learning of observation functions in state-space models by nonparametric moment methods Journal Article
In: Foundations of Data Science, 2023.
Links | BibTeX | Tags: computational mathematics, hidden Markov models, inverse problems, Machine learning, optimal transport, regression, statistics, stochastic systems, Unsupervised Learning
@article{nokey,
title = {Unsupervised learning of observation functions in state-space models by nonparametric moment methods},
author = {Qingci An and Yannis Kevrekidis and Fei Lu and Mauro Maggioni},
url = {https://arxiv.org/abs/2207.05242
https://doi.org/10.3934/fods.2023002},
doi = {10.3934/fods.2023002},
year = {2023},
date = {2023-02-01},
urldate = {2023-02-01},
journal = {Foundations of Data Science},
keywords = {computational mathematics, hidden Markov models, inverse problems, Machine learning, optimal transport, regression, statistics, stochastic systems, Unsupervised Learning},
pubstate = {published},
tppubtype = {article}
}
2019
Little, Anna V; Maggioni, Mauro; Murphy, James M
Path-Based Spectral Clustering: Guarantees, Robustness to Outliers, and Fast Algorithms Journal Article
In: Journ. Mach. Learn. Res., vol. 21, pp. 1-66, 2019.
Links | BibTeX | Tags: Clustering, diffusion geometry, Machine learning, Unsupervised Learning
@article{PathBasedSpectralClustering,
title = {Path-Based Spectral Clustering: Guarantees, Robustness to Outliers, and Fast Algorithms},
author = {Anna V Little and Mauro Maggioni and James M Murphy},
url = {http://jmlr.csail.mit.edu/papers/volume21/18-085/18-085.pdf},
year = {2019},
date = {2019-01-01},
journal = {Journ. Mach. Learn. Res.},
volume = {21},
pages = {1-66},
keywords = {Clustering, diffusion geometry, Machine learning, Unsupervised Learning},
pubstate = {published},
tppubtype = {article}
}
Maggioni, Mauro; Murphy, James M
Learning by active nonlinear diffusion Journal Article
In: Foundations of Data Science, vol. 1, no. “2639-8001-2019-3-271”, pp. 271, 2019, ISSN: A0000-0002.
Links | BibTeX | Tags: Active Learning, Clustering, diffusion geometry, Machine learning, Unsupervised Learning
@article{2639-8001_2019_3_271,
title = {Learning by active nonlinear diffusion},
author = {Mauro Maggioni and James M Murphy},
url = {http://aimsciences.org//article/id/6f8fefb2-e464-48ea-b2de-f37686725966},
doi = {10.3934/fods.2019012},
issn = {A0000-0002},
year = {2019},
date = {2019-01-01},
journal = {Foundations of Data Science},
volume = {1},
number = {"2639-8001-2019-3-271"},
pages = {271},
keywords = {Active Learning, Clustering, diffusion geometry, Machine learning, Unsupervised Learning},
pubstate = {published},
tppubtype = {article}
}
Vogelstein, Joshua T; Bridgeford, Eric W; Wang, Qing; Priebe, Carey E; Maggioni, Mauro; Shen, Cencheng
Discovering and deciphering relationships across disparate data modalities Journal Article
In: eLife, pp. 8:e41690, 2019.
Links | BibTeX | Tags: Machine learning, statistics, Unsupervised Learning
@article{MAGC,
title = {Discovering and deciphering relationships across disparate data modalities},
author = {Joshua T Vogelstein and Eric W Bridgeford and Qing Wang and Carey E Priebe and Mauro Maggioni and Cencheng Shen},
url = {https://elifesciences.org/articles/41690},
doi = {10.7554/eLife.41690},
year = {2019},
date = {2019-01-01},
journal = {eLife},
pages = {8:e41690},
keywords = {Machine learning, statistics, Unsupervised Learning},
pubstate = {published},
tppubtype = {article}
}
2018
Murphy, James M; Maggioni, Mauro
Diffusion geometric methods for fusion of remotely sensed data Proceedings Article
In: Velez-Reyes, Miguel; Messinger, David W (Ed.): Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV, pp. 137 – 147, International Society for Optics and Photonics SPIE, 2018.
Links | BibTeX | Tags: Active Learning, Clustering, diffusion geometry, hyperspectral imaging, imaging, Machine learning, Unsupervised Learning
@inproceedings{10.1117/12.2305274,
title = {Diffusion geometric methods for fusion of remotely sensed data},
author = {James M Murphy and Mauro Maggioni},
editor = {Miguel Velez-Reyes and David W Messinger},
url = {https://doi.org/10.1117/12.2305274},
doi = {10.1117/12.2305274},
year = {2018},
date = {2018-01-01},
urldate = {2018-01-01},
booktitle = {Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV},
volume = {10644},
pages = {137 -- 147},
publisher = {SPIE},
organization = {International Society for Optics and Photonics},
keywords = {Active Learning, Clustering, diffusion geometry, hyperspectral imaging, imaging, Machine learning, Unsupervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
2016
Shen, Cencheng; Priebe, Carey E; Maggioni, Mauro; Vogelstein, Joshua T
Dependence Discovery from Multimodal Data via Multiscale Generalized Correlation Journal Article
In: Submitted, 2016.
BibTeX | Tags: Machine learning, statistics, Unsupervised Learning
@article{ShenEtAl2016,
title = {Dependence Discovery from Multimodal Data via Multiscale Generalized Correlation},
author = {Cencheng Shen and Carey E Priebe and Mauro Maggioni and Joshua T Vogelstein},
year = {2016},
date = {2016-01-01},
journal = {Submitted},
keywords = {Machine learning, statistics, Unsupervised Learning},
pubstate = {published},
tppubtype = {article}
}
2012
Chen, Guangliang; Iwen, Mark A; Chin, Peter S; Maggioni, Mauro
A fast multiscale framework for data in high-dimensions: Measure estimation, anomaly detection, and compressive measurements Proceedings Article
In: Visual Communications and Image Processing (VCIP), 2012 IEEE, pp. 1-6, 2012.
BibTeX | Tags: Clustering, diffusion geometry, Machine learning, Unsupervised Learning
@inproceedings{6410789,
title = {A fast multiscale framework for data in high-dimensions: Measure estimation, anomaly detection, and compressive measurements},
author = {Guangliang Chen and Mark A Iwen and Peter S Chin and Mauro Maggioni},
year = {2012},
date = {2012-01-01},
booktitle = {Visual Communications and Image Processing (VCIP), 2012 IEEE},
pages = {1-6},
keywords = {Clustering, diffusion geometry, Machine learning, Unsupervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
Chen, Guangliang; Iwen, Mark A; Chin, Peter S; Maggioni, Mauro
A Fast Multiscale Framework for Data in High Dimensions: Measure Estimation, Anomaly Detection, and Compressive Measurements Proceedings Article
In: Visual Communications and Image Processing (VCIP), 2012 IEEE, pp. 1-6, 2012.
Links | BibTeX | Tags: Clustering, diffusion geometry, Machine learning, Unsupervised Learning
@inproceedings{CIMC:vcip2012,
title = {A Fast Multiscale Framework for Data in High Dimensions: Measure Estimation, Anomaly Detection, and Compressive Measurements},
author = {Guangliang Chen and Mark A Iwen and Peter S Chin and Mauro Maggioni},
url = {https://users.math.msu.edu/users/iwenmark/Papers/vcip2012.pdf},
doi = {10.1109/VCIP.2012.6410789},
year = {2012},
date = {2012-01-01},
urldate = {2012-01-01},
booktitle = {Visual Communications and Image Processing (VCIP), 2012 IEEE},
pages = {1-6},
keywords = {Clustering, diffusion geometry, Machine learning, Unsupervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
2006
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}
}
2004
Maggioni, Mauro; Warner, F J; Davis, Gus L; Coifman, Ronald R; Geshwind, Frank B; Coppi, Andreas C; DeVerse, R A
Algorithms from Signal and Data Processing Applied to Hyperspectral Analysis: Application to Discriminating Normal and Malignant Microarray Colon Tissue Sections Technical Report
Yale University Dept. Comp. Sci., no. 1311, 2004.
BibTeX | Tags: Clustering, diffusion geometry, hyperspectral imaging, imaging, Machine learning, Unsupervised Learning
@techreport{MMPathTechRep,
title = {Algorithms from Signal and Data Processing Applied to Hyperspectral Analysis: Application to Discriminating Normal and Malignant Microarray Colon Tissue Sections},
author = {Mauro Maggioni and F J Warner and Gus L Davis and Ronald R Coifman and Frank B Geshwind and Andreas C Coppi and R A DeVerse},
year = {2004},
date = {2004-02-01},
urldate = {2004-02-01},
number = {1311},
address = {Dept. Comp. Sci.},
institution = {Yale University},
keywords = {Clustering, diffusion geometry, hyperspectral imaging, imaging, Machine learning, Unsupervised Learning},
pubstate = {published},
tppubtype = {techreport}
}
Maggioni, Mauro; Warner, F J; Davis, Gus L; Coifman, Ronald R; Geshwind, Frank B; Coppi, Andreas C; DeVerse, R A
Algorithms from Signal and Data Processing Applied to Hyperspectral Analysis: Application to Discriminating Normal and Malignant Microarray Colon Tissue Sections Journal Article
In: submitted, 2004.
BibTeX | Tags: Clustering, diffusion geometry, hyperspectral imaging, imaging, Machine learning, Unsupervised Learning
@article{MMIEEEPath,
title = {Algorithms from Signal and Data Processing Applied to Hyperspectral Analysis: Application to Discriminating Normal and Malignant Microarray Colon Tissue Sections},
author = {Mauro Maggioni and F J Warner and Gus L Davis and Ronald R Coifman and Frank B Geshwind and Andreas C Coppi and R A DeVerse},
year = {2004},
date = {2004-01-01},
urldate = {2004-01-01},
journal = {submitted},
keywords = {Clustering, diffusion geometry, hyperspectral imaging, imaging, Machine learning, Unsupervised Learning},
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.