MAURO MAGGIONI

PUBLICATIONS

Papers : divided into categories: Math/Applied math, Markov Decision Processes, Hyperspectral pathology and Medicine

Finance, Miscellanea

Talks

Tutorials

Google Scholar    Papers on the ArXiv

PAPERS

Math/Applied Math

• Geometric Multiscale Reduction for Autonomous and Controlled Nonlinear Systems, J. Bouvrie and M. Maggioni, IEEE Conference on Decision and Control (CDC), 2012.
• Multiscale Geometric Methods for Data Sets I: Multiscale SVD, Noise and Curvature, A. V. Little, M. Maggioni, L. Rosasco. This paper summarizes the work in A.V. Little's thesis (May 2011) on multi scale singular values for noisy point clouds. This extends the analysis of the constructions and results in our previous work Multiscale Estimation of Intrinsic Dimensionality of Data Sets (A.V. Little and Y.-M. Jung and M. Maggioni, Proc. AAAI, 2009, and see a presentation by A.V. Little here) and Estimation of intrinsic dimensionality of samples from noisy low-dimensional manifolds in high dimensions with multiscale SVD (A.V. Little and J. Lee and Y.-M. Jung and M. Maggioni, Proc. SSP, 2009}
• Approximation of Points on Low-Dimensional Manifolds Via Random Linear Projections, M. Iwen, M. Maggioni. Appears here in Information & Inference, submitted Apr 2012.
• A Fast Multiscale Framework for Data in High Dimensions: Measure Estimation, Anomaly Detection, and Compressive Measurements, G. Chen and M. Iwen and S. Chin and M. Maggioni, Visual Communications and Image Processing (VCIP), 2012 IEEE (submitted April 2012).
• What is...Data Mining?, M. Maggioni , A.M.S. Notices, April 2012
• Multiscale Analysis of Plane Arrangements, G. Chen, M. Maggioni, CVPR, 2011. See also the corresponding poster and code on G. Chen's webpage.
• Multiscale Geometric Methods for Data Sets II: Geometric Wavelets, W.K. Allard, G. Chen, M. Maggioni , Appl. Comp. Harm. Anal., Vol. 32(3), May 2012, 435-462.
• Determination of reaction coordinates via locally scaled diffusion map, M. A. Rohrdanz, W. Zheng, M. Maggioni, C. Clementi, J. Chem. Phys., 134 2011: 124116
• Polymer reversal rate calculated via locally scaled diffusion map, W. Zheng, M. A. Rohrdanz, M. Maggioni, C. Clementi, J. Chem. Phys., 134 2011: 144108
• Some Recent Advances in the Geometric Analysis of Point Clouds in High Dimensions, G. Chen, A.V. Little, M. Maggioni and L. Rosasco, in Wavelets and Multiscale Analysis: Theory and Applications, March 2011, Springer
• Exploration and Representation of Data with Geometric Wavelets, Eric E Monson, Rachael Brady, Guangliang Chen, Mauro Maggioni, Poster and short paper at Visweek 2010
• Justin Guinney, Phillip Febbo, Mauro Maggioni, Sayan Mukherjee, Multiscale factor models for molecular networks, JSM Proc. (2010), pp. 4887-4901, A.S.A.
• Learning gradients: predictive models that infer geometry and statistical dependence, Q. Wu, J. Guinney, M. Maggioni, S. Mukherjee, J.M.L.R., vol. 11 (August, 2010), pp. 2175-2198
• Multiscale Geometric Dictionaries for point-cloud data, G. Chen, M. Maggioni, Proc. SampTA 2011
• Multiscale Analysis of Time Series of Graphs, J. Lee, M. Maggioni, Proc. SampTA 2011
• Multiscale Geometric Methods for estimating intrinsic dimension, A.V. Little, M. Maggioni, L. Rosasco, Proc. SampTA 2011
• Universal Local Parametrizations via Heat Kernels and Eigenfunctions of the Laplacian, P.W. Jones, M. Maggioni, R. Schul, Ann. Acad. Scient. Fen., Vol. 35:1-44, 2010. A short version has appeared in P.N.A.S here. Localized eigenfunctions appear incidentally in this paper. See Terry Tao's discussion on scarring for the Bunimovich stadium and the pictures by Denis Grebenkov here. More pictures and talks about Laplacian eigenfunctions can be found on Naoki Saito's page on the ICIAM minisymposium on Laplacian eigenfunctions and their applications. See also D. Stone's page, and in particular his paper on Modes of wave-chaotic dielectric resonators.
• GeometryAnalysis and Signal Processing on Digital Data,Emergent Structures, and Knowledge Building , R.R. Coifman, M.Maggioni, Siam News, Dec. 2008.
• A general framework for adaptive regularization based on diffusion processes on graphs , A.D. Szlam, M. Maggioni, R.R. Coifman. J.M.L.R., 9 (2008) 1711-1739 (published, shortened version here).
• Multiscale Analysis of Data Sets using Diffusion Wavelets, M.Maggioni and R.R. Coifman, Proc. Data Mining for BIOmedical Informatics.
• Diffusion Polynomial Frames on measure metric spaces, M. Maggioni, H.N. Mhaskar. Appl. Comp. Harm. Anal., 24(3): 329--353, 2007.
• Tensor-CUR Decompositions for Tensor-Based Data, M Mahoney, M Maggioni, and P Drineas. to appear in SIAM Jour. on Mat. Anal. and Appl., 2007.
• Geometries of sensor outputs, inference and information processing, R.R. Coifman, S Lafon, M Maggioni, Y Keller, AD Szlam, F J Warner, S W Zucker. Proc. SPIE, Vol. 6232, 623204, May 2006.
• Geometric diffusions for the analysis of data from sensor networks, RR Coifman, M Maggioni, SW Zucker, and IG Kevrekidis. Curr. Opin. Neurobiol., 15(5):576--84, October 2005.
• Biorthogonal diffusion wavelets for multiscale representations on manifolds and graphs , M Maggioni, JC Bremer Jr, RR Coifman, and AD Szlam. Proc. SPIE Wavelet XI, Vol 5914, 59141M, Sep 2005.
• Diffusion-driven multiscale analysis on manifolds and graphs:top-down and bottom-up constructions , M Maggioni, AD Szlam, RR Coifman, and JC Bremer Jr. Proc. SPIE Wavelet XI, Vol 5914, 59141D, Sep 2005.
• Diffusion wavelet packets, JC Bremer, RR Coifman, M Maggioni, and AD Szlam. Appl. Comp. Harm. Anal., 15(1): 95--112.
• Diffusion wavelets for multiscale analysis on graphs and manifolds, RR Coifman and M Maggioni. Proc. Conf. Interactions Splines and Wavelets, Oct. 2005.
• Diffusion wavelets, RR Coifman and M Maggioni. Appl. Comp. Harm. Anal., 21(1):53--94, July 2006.
• Geometric diffusions as a tool for harmonic analysis and structure definition of data. part i: Diffusion maps , RR Coifman, S Lafon, A Lee, M Maggioni, B Nadler, FJ Warner, and SW Zucker. Proc. of Nat. Acad. Sci., 102:7426--7431, May 2005.
• Geometric diffusions as a tool for harmonic analysis and structure definition of data. part ii: Multiscale methods , RR Coifman, S Lafon, A Lee, M Maggioni, B Nadler, FJ Warner, and SW Zucker. Proc. of Nat. Acad. Sci., 102:7432--7438, May 2005.
• Multiresolution analysis associated to diffusion semigroups: construction and fast algorithms , RR Coifman and M Maggioni. Tech. Rep. YALE/DCS/TR-1292, Dept. Comp. Sci., Yale University, June 2004. This has been superceded by Diffusion Wavelets.
• Wavelet frames on groups and hypergroups via discretization of Calder\'on formulas , M Maggioni. Monats. Mat., (143):299--331, 2004.
• On the box problem, NH Katz, E Krop, and M Maggioni, Math. Research Letters, 4:515--519, 2002.
• M-band Burt-Adelson wavelets, M Maggioni, Appl. Comput. Harm. Anal., 3:286--311, 2000.
• Characterization of tight wavelet frames with arbitrary matrix dilations and tightness preserving oversampling , CK Chui, W Czaja, M Maggioni, and GL Weiss, J Four Anal App, 8(2):173--200, 2002.
• Critical exponent of short even filters and biorthogonal Burt-Adelson wavelets , M Maggioni, Monats. Math., 131(1):49--70, 2000.
  

Markov Decision Processes, Learning, Artificial Intelligence

• Multiscale Markov Decision Problems: Compression, Solution, and Transfer Learning, J. Bouvrie, M. Maggioni, 2012, submitted.
• Efficient Solution of Markov Decision Problems with Multiscale Representations, J. Bouvrie and M. Maggioni, Proc. 50th Annual Allerton Conference on Communication, Control, and Computing, 2012.
• Proto-value Functions: A Laplacian Framework for Learning Representation and Control in Markov Decision Processes , S Mahadevan, M Maggioni. J.M.L.R., 2007.
• Multiscale Diffusion Bases for Policy Iteration in Markov Decision Processes, M Maggioni, S Mahadevan. Submitted, 2006.
• Simultaneous Learning of Representation and Control In Continuous Domains, S Mahadevan, Kimberly Ferguson, Sarah Osentoski and M Maggioni, AAAI 2006.
• A Multiscale Framework For Markov Decision Processes using Diffusion Wavelets , M Maggioni and S Mahadevan, Univ. of Mass., Dept. of Computer Science TR-2006-36, and ICML 2005.
• Value function approximation with diffusion wavelets and Laplacian eigenfunctions , S Mahadevan and M Maggioni, Univ. of Massachusetts, Dept. of Computer Science TR-2005-38, and NIPS}, 2005.
• Fast Direct Policy Evaluation Using Multiscale Markov Diffusion Processes , M Maggioni and S Mahadevan , Univ. of Mass., Dept. of Computer Science, TR-2005-39, and NIPS, 2005.

Hyperspectral Imaging, Pathology & Medical Applications

• Hyperspectral Microscopic Analysis of Normal, Adenoma and Carcinoma Microarray Tissue Sections, M Maggioni, FJ Warner, GL Davis, RR Coifman, FB Geshwind, AC Coppi, and RA DeVerse, SPIE Optical Biopsy, 2006, Vol. 6091, 60910I, available here.
• QEEG-based classification with wavelet packets and microstate features for triage applications in the ER , E Causevic, RR Coifman, R Isenhart, A Jacquin, ER John, M Maggioni, LS Prichep, FJ Warner, ICASSP, 2006. Here is a preprint of the poster.
• Algorithms from signal and data processing applied to hyperspectralanalysis: Application to discriminating normal and malignant microarray colon tissue sections , M Maggioni, FJ Warner, GL Davis, RR Coifman, FB Geshwind, AC Coppi, and RA DeVerse, submitted, 2004.
• Algorithms from signal and data processing applied to hyperspectral analysis: Application to discriminating normal and malignant microarray colon tissue sections , M Maggioni, FJ Warner, GL Davis, RR Coifman, FrankB Geshwind, AndreasC Coppi, and RichardA DeVerse, Tech. Rep. 1311, Yale University, Dept. Comp. Sci., Feb 2004.
• Hyper-spectral analysis of normal and malignant colon tissue microarray sections using a novel dmd system , GL Davis, M Maggioni, FJ Warner, FB Geshwind, AC Coppi, RA DeVerse, and RR Coifman, Poster, Optical Imaging NIH workshop, Sep 2004.

Finance

• Beauty is in the bid of the beholder: an empirical basis for style, W N Goetzmann, P W Jones, M Maggioni, J Walden, submitted, Sept. 2004.

Miscellanea

• Auditory display of hyperspectral colon tissue images using vocal synthesis models, RJ Cassidy, JBerger, M Maggioni, and RR Coifman, Proc. 2004 Intern. Conf. Auditory Display}, 2004.
• Multi-scale approximation with hierarchical radial basis functions networks , S Ferrari, M Maggioni, and NA Borghese, IEEE Trans. on Neural Networks, 15(1):178--188, January 2004.
  

TALKS

• Series of Wing Lectures at the University of Rochester: Lecture 1, 2, 3, 4/17-18-19/13, University of Rochester.
• Two talks given at SoCG 2012: Geometric estimation of intrinsically low-dimensional probability measures in high dimensions, within the Minisymposium on Computational Geometric Learning, and Multiscale SVD and Geometric Multi-Resolution Analysis for noisy point clouds in high dimensions, within the Minisymposium on Connections between analysis and computational geometry. June 2012, Chapel Hill.
• Digital data sets: Geometry, random walks, multiscale analysis, and applications, invited plenary talk at A.M.S. sectional meeting in Tampa, March 2012.
• Harmonic and Multiscale Analysis of and on Data sets, invited talk, 6/1/09, TTI Chicago
• Harmonic and Multiscale Analysis of and on Data sets, invited talk, 5/19/09, SAMPTA, C.I.R.M., Luminy, France.
• Harmonic and Multiscale Analysis of and on Data sets, invited talk, 5/16/09, 20 Years of Wavelets, Chicago.
• Parametrizations of manifolds via Laplacian eigenfunctions and heat kernels, 4/21/09, Duke Geometry Seminar.
• Analysis of High-dimensional Data Sets and Graphs, 3/21/09, Visiting graduate students day.
• Parametrizations of Manifolds with Laplacian Eigenfunctions and Heat Kernels, 2/09/09, invited talk, I.P.A.M., Workshop on Laplacian eigenfunctions.
• Harmonic and multiscale analysis of and on data sets in high dimensions, 6/12/08, invited talk, I.M.S. at N.U.S. in Singapore.
• Multiscale Analysis on graphs via diffusion, 5/14/08, DIMACS.
• Analysis on and analysis of data sets with diffusion operators, 4/14/08, CAAM, Rice Univ, 4/24/08, Univ. of Maryland College Park.
• Geometry of data sets in high dimensions and learning, 4/11/08, Visualization Forum, Duke Univ.
• Geometry of data sets in high dimensions and learning, 4/8/08, O.N.R. workshop, Naval Postgraduate School, Monterey, CA.
• Harmonic Analysis on data sets in high-dimensional space, 3/3/08, Parametrizations of manifolds with heat kernels, multiscale analysis on graphs, and applications to analysis of data sets , 3/5/08, SC/IMI, Columbia, SC.
• Diffusion analysis of and on data sets through diffusion operators, 1/07/08, AMS, San Diego.
• Diffusion analysis of and on data sets through diffusion operators, 11/02/07, UNC.
• CDI NSF program panelist short presentation, 10/29/07, IPAM in UCLA.
• Diffusion analysis of and on data sets through diffusion operators, conference on Geometric and Topological Approaches to Data Analysis, 10/08/07, TTI.
• Diffusion analysis of and on graphs, and high-dimensional data , conference on Dynamic Searches and Knowledge Building, 10/03/07, IPAM in UCLA.
• Diffusion analysis of and on graphs, and high-dimensional data , conference on Trends in Applied Harmonic Analysis, 9/27/07, Banff International Research Station in Banff.
• Diffusion analysis of and on graphs, and high-dimensional data , talk given at the minisymposium on Eigenfunctions of the Laplacian, held at ICIAM 2007.
• Diffusion processes on graphs and multiscale analysis on data sets in high-dimensions, invited talk given at the Twelth International Conference in Approximation Theory in San Antonio, Texas, March 6th, 2007.
• Analisi armonica multiscala applicata all'analisi di dati digitali in alte dimensioni e su grafi, Universita' degli Studi Milano-Bicocca, Dec. 20th, 2006.
• Diffusion processes on graphs, analysis of high-dimensional data, applications to imaging, Duke Univ., Oct. 11th, 2006
• Diffusion Wavelets for multiscale analysis on manifolds and graphs: constructions and applications, Duke Univ., Nov. 7th, 2005
• Diffusion Wavelets on Graphs and Manifolds, TTI Chicago, 2005.
  

TUTORIALS

• 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.

The material presented at this web site is partially based upon work supported by the Alfred P. Sloan Foundation and the National Science Foundation. Any opinions, findings and conclusions or recomendations expressed in this material are those of the author and do not necessarily reflect the views of the granting agencies.