2011
|
Zheng, W; Rohrdanz, M A; Maggioni, Mauro; Clementi, Cecilia Polymer reversal rate calculated via locally scaled diffusion map Journal Article J. Chem. Phys., (134), pp. 144108, 2011. BibTeX | Tags: diffusion geometry, Machine learning, Manifold Learning, molecular dynamics, stochastic systems @article{ZRMC:PolymerReversal,
title = {Polymer reversal rate calculated via locally scaled diffusion map},
author = {W Zheng and M A Rohrdanz and Mauro Maggioni and Cecilia Clementi},
year = {2011},
date = {2011-01-01},
journal = {J. Chem. Phys.},
number = {134},
pages = {144108},
keywords = {diffusion geometry, Machine learning, Manifold Learning, molecular dynamics, stochastic systems},
pubstate = {published},
tppubtype = {article}
}
|
Rohrdanz, M A; Zheng, W; Maggioni, Mauro; Clementi, Cecilia Determination of reaction coordinates via locally scaled diffusion map Journal Article J. Chem. Phys., (134), pp. 124116, 2011. BibTeX | Tags: diffusion geometry, Machine learning, Manifold Learning, molecular dynamics, stochastic systems @article{RZMC:ReactionCoordinatesLocalScaling,
title = {Determination of reaction coordinates via locally scaled diffusion map},
author = {M A Rohrdanz and W Zheng and Mauro Maggioni and Cecilia Clementi},
year = {2011},
date = {2011-01-01},
journal = {J. Chem. Phys.},
number = {134},
pages = {124116},
keywords = {diffusion geometry, Machine learning, Manifold Learning, molecular dynamics, stochastic systems},
pubstate = {published},
tppubtype = {article}
}
|
Chen, Guangliang; Maggioni, Mauro Multiscale Geometric Dictionaries for Point-Cloud Data Inproceedings 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 Inproceedings 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
|
Monson, Eric; Chen, Guangliang; Brady, Rachel; Maggioni, Mauro Data representation and exploration with Geometric Wavelets Inproceedings Visual Analytics Science and Technology (VAST), 2010 IEEE Symposium, pp. 243–244, 2010. Links | BibTeX | Tags: geometric wavelets, visualization @inproceedings{MM:Vast2010,
title = {Data representation and exploration with Geometric Wavelets},
author = {Eric Monson and Guangliang Chen and Rachel Brady and Mauro Maggioni},
doi = {10.1109/VAST.2010.5653822},
year = {2010},
date = {2010-12-01},
booktitle = {Visual Analytics Science and Technology (VAST), 2010 IEEE Symposium},
pages = {243–244},
keywords = {geometric wavelets, visualization},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Jones, Peter W; Maggioni, Mauro; Schul, Raanan Universal local manifold parametrizations via heat kernels and eigenfunctions of the Laplacian Journal Article Ann. Acad. Scient. Fen., 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}
}
|
Guinney, J; Febbo, P; Maggioni, Mauro; Mukherjee, S Multiscale factor models for molecular networks Journal Article Proc. JSM, 2010. BibTeX | Tags: spectral clustering @article{GFMS:MultiscaleMolecularNetworks,
title = {Multiscale factor models for molecular networks},
author = {J Guinney and P Febbo and Mauro Maggioni and S Mukherjee},
year = {2010},
date = {2010-01-01},
journal = {Proc. JSM},
keywords = {spectral clustering},
pubstate = {published},
tppubtype = {article}
}
|
Chen, Guangliang; Maggioni, Mauro Multiscale Geometric Methods for Data Sets III: multiple planes Journal Article 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 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}
}
|
Monson, Eric; Chen, Guangliang; Brady, Rachel; Maggioni, Mauro Data Representation and Exploration with Geometric Wavelets Inproceedings Proceedings of the IEEE Symposium on Visual Analytics Science and Technology (VAST), 2010. BibTeX | Tags: geometric wavelets, visualization @inproceedings{Monson:VAST2010,
title = {Data Representation and Exploration with Geometric Wavelets},
author = {Eric Monson and Guangliang Chen and Rachel Brady and Mauro Maggioni},
year = {2010},
date = {2010-01-01},
booktitle = {Proceedings of the IEEE Symposium on Visual Analytics Science and Technology (VAST)},
keywords = {geometric wavelets, visualization},
pubstate = {published},
tppubtype = {inproceedings}
}
|
2009
|
Little, Anna V; Jung, Y -M; Maggioni, Mauro Multiscale Estimation of Intrinsic Dimensionality of Data Sets Inproceedings 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 $SVD$ Inproceedings 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}
}
|
Willinger, Walter; Rejaie, Reza; Torkjazi, M; Valafar, M; Maggioni, Mauro Research on Online Social Networks: Time to Face the Real Challenges Inproceedings Proc. 2nd Workshop on Hot Topics in Measurement and Modeling of Computer Systems (HotMetrics’09), 2009. BibTeX | Tags: @inproceedings{wrm:OnlineSocial,
title = {Research on Online Social Networks: Time to Face the Real Challenges},
author = {Walter Willinger and Reza Rejaie and M Torkjazi and M Valafar and Mauro Maggioni},
year = {2009},
date = {2009-01-01},
booktitle = {Proc. 2nd Workshop on Hot Topics in Measurement and Modeling of Computer Systems (HotMetrics’09)},
keywords = {},
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}
}
|
Szlam, Arthur D; Maggioni, Mauro; Coifman, Ronald R Regularization on Graphs with Function-adapted Diffusion Processes Journal Article Jour. Mach. Learn. Res., (9), pp. 1711–1739, 2008, ((YALE/DCS/TR1365, Yale Univ, July 2006)). 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},
year = {2008},
date = {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}
}
|
Maggioni, Mauro; Mhaskar, Hrushikesh Diffusion polynomial frames on metric measure spaces Journal Article ACHA, 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 Proc. Nat. Acad. Sci., 105 (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}
}
|
Coifman, Ronald R; Kevrekidis, Ioannis G; Lafon, Stephane; Maggioni, Mauro; Nadler, Boaz Diffusion Maps, reduction coordinates and low dimensional representation of stochastic systems Journal Article SIAM J.M.M.S., 7 (2), pp. 842–864, 2008. BibTeX | Tags: diffusion geometry, dynamical systems, Laplacian eigenfunctions, Machine learning, model reduction, stochastic systems @article{CKLMN:DiffusionMapsReductionCoordinates,
title = {Diffusion Maps, reduction coordinates and low dimensional representation of stochastic systems},
author = {Ronald R Coifman and Ioannis G Kevrekidis and Stephane Lafon and Mauro Maggioni and Boaz Nadler},
year = {2008},
date = {2008-01-01},
journal = {SIAM J.M.M.S.},
volume = {7},
number = {2},
pages = {842–864},
keywords = {diffusion geometry, dynamical systems, Laplacian eigenfunctions, Machine learning, model reduction, stochastic systems},
pubstate = {published},
tppubtype = {article}
}
|
2007
|
Coifman, Ronald R; Maggioni, Mauro Multiscale Data Analysis with Diffusion Wavelets Journal Article 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 JMLR, 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 Appl. Comp. Harm. Anal., 21 (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 Appl. Comp. Harm. Anal., 21 (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 Inproceedings Athale, John Zolper; Eds. Intelligent Integrated Microsystems; Ravindra C 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}
}
|
Causevic, E; Coifman, Ronald R; Isenhart, R; Jacquin, A; John, E R; Maggioni, Mauro; Prichep, L S; Warner, F J QEEG-based classification with wavelet packets and microstate features for triage applications in the ER Inproceedings ICASSP Proc., 2006, (10.1109/ICASSP.2006.1660859). BibTeX | Tags: Clustering, hidden Markov models, Machine learning @inproceedings{MM:EEG,
title = {QEEG-based classification with wavelet packets and microstate features for triage applications in the ER},
author = {E Causevic and Ronald R Coifman and R Isenhart and A Jacquin and E R John and Mauro Maggioni and L S Prichep and F J Warner},
year = {2006},
date = {2006-05-01},
volume = {3},
publisher = {ICASSP Proc.},
note = {10.1109/ICASSP.2006.1660859},
keywords = {Clustering, hidden Markov models, Machine learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
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}
}
|
Maggioni, Mauro; Mahadevan, Sridhar Fast Direct Policy Evaluation using Multiscale Analysis of Markov Diffusion Processes Inproceedings 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 Inproceedings 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}
}
|
Maggioni, Mauro; Davis, Gus L; Warner, F J; Geshwind, Frank B; Coppi, Andreas C; DeVerse, R A; Coifman, Ronald R Hyperspectral microscopic analysis of normal, benign and carcinoma microarray tissue sections Conference 6091 (1), SPIE, San Jose, CA, USA, 2006. BibTeX | Tags: Clustering, hyperspectral imaging, imaging, Machine learning, supervised learning @conference{maggioni:60910I,
title = {Hyperspectral microscopic analysis of normal, benign and carcinoma microarray tissue sections},
author = {Mauro Maggioni and Gus L Davis and F J Warner and Frank B Geshwind and Andreas C Coppi and R A DeVerse and Ronald R Coifman},
editor = {Robert R Alfano and Alvin Katz},
year = {2006},
date = {2006-01-01},
journal = {Optical Biopsy VI},
volume = {6091},
number = {1},
pages = {60910I},
publisher = {SPIE},
address = {San Jose, CA, USA},
keywords = {Clustering, hyperspectral imaging, imaging, Machine learning, supervised learning},
pubstate = {published},
tppubtype = {conference}
}
|
Mahoney, Michael W; Maggioni, Mauro; Drineas, Petros Tensor-CUR Decompositions For Tensor-Based Data Inproceedings Proc 12-th Annual SIGKDD, 2006. BibTeX | Tags: computational mathematics @inproceedings{MMD:TensorCUR,
title = {Tensor-CUR Decompositions For Tensor-Based Data},
author = {Michael W Mahoney and Mauro Maggioni and Petros Drineas},
year = {2006},
date = {2006-01-01},
booktitle = {Proc 12-th Annual SIGKDD},
keywords = {computational mathematics},
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 Curr Opin Neurobiol, 15 (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 Proceedings of the National Academy of Sciences of the United States of America, 102 (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 Proceedings of the National Academy of Sciences of the United States of America, 102 (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 Inproceedings 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 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{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 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
|
Goetzmann, William; Jones, Peter W; Maggioni, Mauro; Walden, Johan Beauty is in the eye of the beholder Journal Article submitted, 2004. BibTeX | Tags: @article{GoetzmannBeauty,
title = {Beauty is in the eye of the beholder},
author = {William Goetzmann and Peter W Jones and Mauro Maggioni and Johan Walden},
year = {2004},
date = {2004-09-01},
journal = {submitted},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Davis, Gus L; Maggioni, Mauro; Warner, F J; Geshwind, Frank B; Coppi, Andreas C; DeVerse, R A; Coifman, Ronald R Hyper-spectral Analysis of normal and malignant colon tissue microarray sections using a novel DMD system Miscellaneous Poster, Optical Imaging NIH workshop, to app. in proc., 2004. BibTeX | Tags: hyperspectral imaging, imaging, medical imaging @misc{PathNIH2004,
title = {Hyper-spectral Analysis of normal and malignant colon tissue microarray sections using a novel DMD system},
author = {Gus L Davis and Mauro Maggioni and F J Warner and Frank B Geshwind and Andreas C Coppi and R A DeVerse and Ronald R Coifman},
year = {2004},
date = {2004-09-01},
howpublished = {Poster, Optical Imaging NIH workshop, to app. in proc.},
keywords = {hyperspectral imaging, imaging, medical imaging},
pubstate = {published},
tppubtype = {misc}
}
|
Coifman, Ronald R; Maggioni, Mauro Multiresolution Analysis associated to diffusion semigroups: construction and fast algorithms Technical Report Dept. Comp. Sci., Yale University (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}
}
|
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., (1311), 2004. BibTeX | Tags: Clustering, diffusion geometry, hyperspectral images, 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},
number = {1311},
address = {Dept. Comp. Sci.},
institution = {Yale University},
keywords = {Clustering, diffusion geometry, hyperspectral images, Machine learning, Unsupervised Learning},
pubstate = {published},
tppubtype = {techreport}
}
|
Ferrari, S; Maggioni, Mauro; Borghese, N A Multi-Scale Approximation with Hierarchical Radial Basis Functions Networks, Journal Article IEEE Trans. on Neural Networks, 15 (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}
}
|
Cassidy, Ryan J; Berger, Jim; Maggioni, Mauro; Coifman, Ronald R Auditory display of hyperspectral colon tissue images using vocal synthesis models Journal Article Proc. 2004 Intern. Con. Auditory Display, 2004. BibTeX | Tags: Clustering, diffusion geometry, hyperspectral images, Machine learning @article{AuditoryDisplay,
title = {Auditory display of hyperspectral colon tissue images using vocal synthesis models},
author = {Ryan J Cassidy and Jim Berger and Mauro Maggioni and Ronald R Coifman},
year = {2004},
date = {2004-01-01},
journal = {Proc. 2004 Intern. Con. Auditory Display},
keywords = {Clustering, diffusion geometry, hyperspectral images, Machine learning},
pubstate = {published},
tppubtype = {article}
}
|
Davis, Gus L; Maggioni, Mauro; Coifman, Ronald R; Levinson, R; Rimm, D Spatial-Spectral Analysis of Colon Carcinoma Journal Article Mod. Path., 2004, (In print). BibTeX | Tags: hyperspectral imaging, imaging, medical imaging @article{ModPath:2003,
title = {Spatial-Spectral Analysis of Colon Carcinoma},
author = {Gus L Davis and Mauro Maggioni and Ronald R Coifman and R Levinson and D Rimm},
year = {2004},
date = {2004-01-01},
journal = {Mod. Path.},
note = {In print},
keywords = {hyperspectral imaging, imaging, medical imaging},
pubstate = {published},
tppubtype = {article}
}
|
Davis, Gus L; Maggioni, Mauro; Warner, F J; Geshwind, Frank B; Coppi, Andreas C; DeVerse, R A; Coifman, Ronald R Spectral Analysis of normal and Malignant Microarray Tissue Sections using a novel micro-optoelectrialmechanical system Journal Article Mod Pathol, 17 (1:358A), 2004. BibTeX | Tags: hyperspectral imaging, imaging, medical imaging @article{ModPath:2004,
title = {Spectral Analysis of normal and Malignant Microarray Tissue Sections using a novel micro-optoelectrialmechanical system},
author = {Gus L Davis and Mauro Maggioni and F J Warner and Frank B Geshwind and Andreas C Coppi and R A DeVerse and Ronald R Coifman},
year = {2004},
date = {2004-01-01},
journal = {Mod Pathol},
volume = {17},
number = {1:358A},
keywords = {hyperspectral imaging, imaging, medical imaging},
pubstate = {published},
tppubtype = {article}
}
|
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 submitted, 2004. BibTeX | Tags: Clustering, diffusion geometry, hyperspectral images, 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},
journal = {submitted},
keywords = {Clustering, diffusion geometry, hyperspectral images, Machine learning, Unsupervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
Maggioni, Mauro Wavelet frames on groups and hypergroups via discretization of Calderón formulas Journal Article Monats. Mat., (143), pp. 299–331, 2004. BibTeX | Tags: harmonic analysis, wavelets @article{MM_WaveletFrames,
title = {Wavelet frames on groups and hypergroups via discretization of Calderón formulas},
author = {Mauro Maggioni},
year = {2004},
date = {2004-01-01},
journal = {Monats. Mat.},
number = {143},
pages = {299–331},
keywords = {harmonic analysis, wavelets},
pubstate = {published},
tppubtype = {article}
}
|
2002
|
Chui, Charles K; Czaja, Wojciech; Maggioni, Mauro; Weiss, Guido Characterization of Tight Wavelet Frames with Arbitrary Matrix Dilations and Tightness Preserving Oversampling Journal Article J Four Anal App, 8 (2), pp. 173-200, 2002. BibTeX | Tags: harmonic analysis, wavelets @article{CCMW,
title = {Characterization of Tight Wavelet Frames with Arbitrary Matrix Dilations and Tightness Preserving Oversampling},
author = {Charles K Chui and Wojciech Czaja and Mauro Maggioni and Guido Weiss},
year = {2002},
date = {2002-01-01},
journal = {J Four Anal App},
volume = {8},
number = {2},
pages = {173-200},
keywords = {harmonic analysis, wavelets},
pubstate = {published},
tppubtype = {article}
}
|
Katz, Nets H; Krop, Elliot; Maggioni, Mauro Remarks on the box problem Journal Article Math. Research Letters, 4 , pp. 515-519, 2002. Links | BibTeX | Tags: combinatorics, harmonic analysis @article{Box,
title = {Remarks on the box problem},
author = {Nets H Katz and Elliot Krop and Mauro Maggioni},
url = {https://core.ac.uk/display/20985482},
year = {2002},
date = {2002-01-01},
journal = {Math. Research Letters},
volume = {4},
pages = {515-519},
keywords = {combinatorics, harmonic analysis},
pubstate = {published},
tppubtype = {article}
}
|
2000
|
Maggioni, Mauro M-Band Burt-Adelson Wavelets Journal Article Appl. Comput. Harm. Anal., 3 , pp. 286-311, 2000. BibTeX | Tags: harmonic analysis, wavelets @article{MBand,
title = {M-Band Burt-Adelson Wavelets},
author = {Mauro Maggioni},
year = {2000},
date = {2000-01-01},
journal = {Appl. Comput. Harm. Anal.},
volume = {3},
pages = {286-311},
keywords = {harmonic analysis, wavelets},
pubstate = {published},
tppubtype = {article}
}
|
Maggioni, Mauro Critical Exponent of Short Even Filters and Biorthogonal Burt-Adelson Wavelets Journal Article Monats. Math., 131 (1), pp. 49-70, 2000. BibTeX | Tags: harmonic analysis, wavelets @article{CriticalExponent,
title = {Critical Exponent of Short Even Filters and Biorthogonal Burt-Adelson Wavelets},
author = {Mauro Maggioni},
year = {2000},
date = {2000-01-01},
journal = {Monats. Math.},
volume = {131},
number = {1},
pages = {49-70},
keywords = {harmonic analysis, wavelets},
pubstate = {published},
tppubtype = {article}
}
|
0000
|
Lu, Fei; Maggioni, Mauro; Tang, Sui Learning interaction kernels in heterogeneous systems of agents from multiple trajectories Journal Article Journ. Mach. Learn. Res., 22 (32), pp. 1–67, 0000. Links | BibTeX | Tags: agent-based models, interacting particle systems, inverse problems, Machine learning, model reduction, statistics @article{LMT:AgentsHeterogeneous,
title = {Learning interaction kernels in heterogeneous systems of agents from multiple trajectories},
author = {Fei Lu and Mauro Maggioni and Sui Tang},
url = {https://jmlr.csail.mit.edu/papers/volume22/19-861/19-861.pdf},
journal = {Journ. Mach. Learn. Res.},
volume = {22},
number = {32},
pages = {1–67},
keywords = {agent-based models, interacting particle systems, inverse problems, Machine learning, model reduction, statistics},
pubstate = {published},
tppubtype = {article}
}
|