Applied Math

Duke Applied Mathematics

Publications of Mauro Maggioni    :recent first  alphabetical  combined  bibtex listing:

Papers Published

  1. Mauro Maggioni, , M-Band Burt-Adelson Wavelets, Appl. Comput. Harm. Anal., vol. 3 (2000), pp. 286-311
  2. Mauro Maggioni, , Critical Exponent of Short Even Filters and Biorthogonal Burt-Adelson Wavelets, Monats. Math., vol. 131 no. 1 (2000), pp. 49-70
  3. Maggioni, M, M-Band Burt-Adelson Biorthogonal Wavelets, Applied and Computational Harmonic Analysis, vol. 9 no. 3 (October, 2000), pp. 286-311, Elsevier BV [doi]  [abs]
  4. Maggioni, M, Critical Exponent of Short Even Filters andBurt-Adelson Biorthogonal Wavelets, Monatshefte F�R Mathematik, vol. 131 no. 1 (November, 2000), pp. 49-69, Springer Nature [doi]  [abs]
  5. Katz, NH; Krop, E; Maggioni, M, On the box problem, Math. Research Letters, vol. 4 (2002), pp. 515-519
  6. Katz, NH; Krop, E; Maggioni, M, Remarks on the box problem, Mathematical Research Letters, vol. 9 no. 4 (January, 2002), pp. 515-519, International Press of Boston [doi]
  7. Chui, CK; Czaja, W; Maggioni, M; Weiss, G, Characterization of general tight wavelet frames with matrix dilations and tightness preserving oversampling, Journal of Fourier Analysis and Applications, vol. 8 no. 2 (August, 2002), pp. 173-200, Springer Nature, ISSN 1069-5869 [doi]  [abs]
  8. Davis, GL; Maggioni, M; Coifman, RR; Levinson, R; Rimm, D, Spatial-Spectral Analysis of Colon Carcinoma, Mod. Path. (2004)
  9. Davis, GL; Maggioni, M; Warner, FJ; Geshwind, FB; Coppi, AC; DeVerse, RA; Coifman, RR, Spectral Analysis of normal and Malignant Microarray Tissue Sections using a novel micro-optoelectrialmechanical system, Mod Pathol, vol. 17 no. 1:358A (2004)
  10. Mauro Maggioni and Frederick J Warner and Gustave L Davis and Ronald R Coifman and Frank B Geshwind and Andreas C Coppi and Richard A DeVerse, Algorithms from Signal and Data Processing Applied to Hyperspectral Analysis: Application to Discriminating Normal and Malignant Microarray Colon Tissue Sections, submitted (2004)
  11. RJ Cassidy and J Berger and Mauro Maggioni and RR Coifman, Auditory display of hyperspectral colon tissue images using vocal synthesis models, Proc. 2004 Intern. Con. Auditory Display (2004)
  12. Ferrari, S; Maggioni, M; Borghese, NA, Multiscale approximation with hierarchical radial basis functions networks., Ieee Transactions on Neural Networks, vol. 15 no. 1 (January, 2004), pp. 178-188, ISSN 1045-9227 [15387258], [doi]  [abs]
  13. Cassidy, RJ; Berger, J; Lee, K; Maggioni, M; Coifman, RR, Analysis of hyperspectral colon tissue images using vocal synthesis models, Conference Record Asilomar Conference on Signals, Systems and Computers, vol. 2 (December, 2004), pp. 1611-1615, ISSN 1058-6393  [abs]
  14. Maggioni, M, Wavelet frames on groups and hypergroups via discretization of calderón formulas, Monatshefte F�R Mathematik, vol. 143 no. 4 (December, 2004), pp. 299-331, Springer Nature [doi]  [abs]
  15. E Causevic and R~R Coifman and R Isenhart and A Jacquin and E~R John and M Maggioni and L~S Prichep and F~J Warner, QEEG-based classification with wavelet packets and microstate features for triage applications in the ER (2005)
  16. Coifman, RR; Lafon, S; Lee, AB; Maggioni, M; Nadler, B; Warner, F; Zucker, SW, Geometric diffusions as a tool for harmonic analysis and structure definition of data: diffusion maps., Proceedings of the National Academy of Sciences of the United States of America, vol. 102 no. 21 (May, 2005), pp. 7426-7431, ISSN 0027-8424 [15899970], [doi]  [abs]
  17. Coifman, RR; Lafon, S; Lee, AB; Maggioni, M; Nadler, B; Warner, F; Zucker, SW, Geometric diffusions as a tool for harmonic analysis and structure definition of data: multiscale methods., Proceedings of the National Academy of Sciences of the United States of America, vol. 102 no. 21 (May, 2005), pp. 7432-7437, ISSN 0027-8424 [15899969], [doi]  [abs]
  18. Coifman, RR; Maggioni, M; Zucker, SW; Kevrekidis, IG, Geometric diffusions for the analysis of data from sensor networks., Current Opinion in Neurobiology, vol. 15 no. 5 (October, 2005), pp. 576-584, ISSN 0959-4388 [16150587], [doi]  [abs]
  19. Szlam, AD; Maggioni, M; Coifman, RR; Bremer, JC, Diffusion-driven multiscale analysis on manifolds and graphs: Top-down and bottom-up constructions, edited by Manos Papadakis and Andrew F. Laine and Michael A. Unser, Smart Structures and Materials 2005: Active Materials: Behavior and Mechanics, vol. 5914 no. 1 (December, 2005), pp. 1-11, SPIE, ISSN 0277-786X [1], [doi]  [abs]
  20. Maggioni, M; Bremer, JC; Coifman, RR; Szlam, AD, Biorthogonal diffusion wavelets for multiscale representations on manifolds and graphs, edited by Manos Papadakis and Andrew F. Laine and Michael A. Unser, Smart Structures and Materials 2005: Active Materials: Behavior and Mechanics, vol. 5914 no. 1 (December, 2005), pp. 1-13, SPIE, ISSN 0277-786X [1], [doi]  [abs]
  21. Mahadevan, S; Maggioni, M, Value function approximation with diffusion wavelets and Laplacian eigenfunctions, in University of Massachusetts, Department of Computer Science Technical Report TR-2005-38; Proc. NIPS 2005, Advances in Neural Information Processing Systems (December, 2005), pp. 843-850, ISSN 1049-5258  [abs]
  22. Sridhar Mahadevan and Kimberly Ferguson and Sarah Osentoski and Mauro Maggioni, Simultaneous Learning of Representation and Control In Continuous Domains, in submitted, Proc. AAAI 2006 (2006)
  23. Arthur D Szlam and Yoel Shkolnisky and James C Bremer and Mauro Maggioni, Image Denoising Via Graph Diffusions, in preparation (2006)
  24. Sridhar Mahadevan and Mauro Maggioni, Proto-value Functions: A Spectral Framework for Solving Markov Decision Processes, submitted (2006)
  25. Peter W Jones and Mauro Maggioni and Raanan Schul, Universal parametrizations via Eigenfunctions of the Laplacian (2006)
  26. Maggioni, M; Davis, GL; Warner, FJ; Geshwind, FB; Coppi, AC; DeVerse, RA; Coifman, RR, Hyperspectral microscopic analysis of normal, benign and carcinoma microarray tissue sections, edited by Robert R. Alfano and Alvin Katz, Progress in Biomedical Optics and Imaging Proceedings of Spie, vol. 6091 no. 1 (May, 2006), pp. 60910I, SPIE, ISSN 1605-7422 [1], [doi]  [abs]
  27. Bremer, JC; Coifman, RR; Maggioni, M; Szlam, AD, Diffusion wavelet packets, Applied and Computational Harmonic Analysis, vol. 21 no. 1 (July, 2006), pp. 95-112, Elsevier BV, ISSN 1063-5203 [doi]  [abs]
  28. Coifman, RR; Maggioni, M, Diffusion wavelets, Applied and Computational Harmonic Analysis, vol. 21 no. 1 (July, 2006), pp. 53-94, Elsevier BV, ISSN 1063-5203 [doi]  [abs]
  29. Coifman, RR; Lafon, S; Maggioni, M; Keller, Y; Szlam, AD; Warner, FJ; Zucker, SW, Geometries of sensor outputs, inference and information processing, in Proc. SPIE, edited by Intelligent Integrated Microsystems; Ravindra A. Athale, John C. Zolper; Eds., Smart Structures and Materials 2005: Active Materials: Behavior and Mechanics, vol. 6232 (September, 2006), pp. 623209, SPIE, ISSN 0277-786X [doi]  [abs]
  30. Maggioni, M; Mahadevan, S, Fast direct policy evaluation using multiscale analysis of Markov diffusion processes, Icml 2006 Proceedings of the 23rd International Conference on Machine Learning, vol. 2006 (October, 2006), pp. 601-608  [abs]
  31. Mahoney, MW; Maggioni, M; Drineas, P, Tensor-CUR decompositions for tensor-based data, in Proc 12-th Annual SIGKDD, Proceedings of the Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, vol. 2006 (October, 2006), pp. 327-336  [abs]
  32. Mahadevan, S; Maggioni, M; Ferguson, K; Osentoski, S, Learning representation and control in continuous Markov decision processes, Proceedings of the National Conference on Artificial Intelligence, vol. 2 (November, 2006), pp. 1194-1199  [abs]
  33. Prichep, LS; Causevic, E; Coifman, RR; Isenhart, R; Jacquin, A; John, ER; Maggioni, M; Warner, FJ, QEEG-based classification with wavelet packet and microstate features for triage applications in the ER, 2015 Ieee International Conference on Acoustics, Speech, and Signal Processing (Icassp), vol. 3 (December, 2006), pp. III1136-III1139, ISSN 1520-6149  [abs]
  34. Maggioni, M; Mahadevan, S, Fast direct policy evaluation using multiscale analysis of markov diffusion processes, in University of Massachusetts, Department of Computer Science Technical Report TR-2005-39; accepted at ICML 2006, Acm International Conference Proceeding Series, vol. 148 (December, 2006), pp. 601-608, ACM Press [doi]  [abs]
  35. Mahadevan, S; Maggioni, M, Proto-value Functions: A Laplacian Framework for Learning Representation and Control, Journ. Mach. Learn. Res. no. 8 (September, 2007)
  36. Mahadevan, S; Maggioni, M, Proto-value functions: A Laplacian framework for learning representation and control in Markov decision processes, Journal of Machine Learning Research, vol. 8 (October, 2007), pp. 2169-2231, ISSN 1532-4435  [abs]
  37. Jones, PW; Maggioni, M; Schul, R, Manifold parametrizations by eigenfunctions of the Laplacian and heat kernels., Proceedings of the National Academy of Sciences of the United States of America, vol. 105 no. 6 (2008), pp. 1803-1808 [18258744], [doi]  [abs]
  38. Maggioni, M; Mhaskar, HN, Diffusion polynomial frames on metric measure spaces, Applied and Computational Harmonic Analysis, vol. 24 no. 3 (May, 2008), pp. 329-353, Elsevier BV, ISSN 1063-5203 [doi]  [abs]
  39. Szlam, AD; Maggioni, M; Coifman, RR, Regularization on graphs with function-adapted diffusion processes, Journal of Machine Learning Research, vol. 9 (August, 2008), pp. 1711-1739, ISSN 1532-4435  [abs]
  40. Szlam, AD; Coifman, RR; Maggioni, M, A general framework for adaptive regularization based on diffusion processes, Journ. Mach. Learn. Res. no. 9 (August, 2008), pp. 1711-1739
  41. Coifman, RR; Lafon, S; Kevrekidis, IG; Maggioni, M; Nadler, B, Diffusion maps, reduction coordinates, and low dimensional representation of stochastic systems, Multiscale Modeling & Simulation, vol. 7 no. 2 (2008), pp. 842-864, Society for Industrial & Applied Mathematics (SIAM), ISSN 1540-3459 [doi]  [abs]
  42. Mahoney, MW; Maggioni, M; Drineas, P, Tensor-CUR decompositions for tensor-based data, Siam Journal on Matrix Analysis and Applications, vol. 30 no. 3 (December, 2008), pp. 957-987, Society for Industrial & Applied Mathematics (SIAM), ISSN 0895-4798 [doi]  [abs]
  43. Little, AV; Jung, YM; Maggioni, M, Multiscale estimation of intrinsic dimensionality of data sets, Aaai Fall Symposium Technical Report, vol. FS-09-04 (December, 2009), pp. 26-33  [abs]
  44. Little, AV; Lee, J; Jung, YM; Maggioni, M, Estimation of intrinsic dimensionality of samples from noisy low-dimensional manifolds in high dimensions with multiscale SVD, Ieee Workshop on Statistical Signal Processing Proceedings (December, 2009), pp. 85-88, IEEE [doi]  [abs]
  45. Guinney, J; Febbo, P; Maggioni, M; Mukherjee, S, Multiscale factor models for molecular networks, JSM Proc. (2010), pp. 4887-4901, American Statistical Association, Alexandria, VA
  46. Eric E Monson, Rachael Brady, Guangliang Chen, Mauro Maggioni, Exploration & Representation of Data with Geometric Wavelets, Poster and short paper at Visweek 2010 (2010)
  47. J. Lee, M. Maggioni, Multiscale Analysis of Time Series of Graphs, Proc. SampTA 2011 (2010)
  48. A.V. Little, M. Maggioni, L. Rosasco, Multiscale Geometric Methods for estimating intrinsic dimension, Proc. SampTA 2011 (2010)
  49. Jones, PW; Maggioni, M; Schul, R, Universal local parametrizations via heat kernels and eigenfunctions of the Laplacian, Annales Academiae Scientiarum Fennicae Mathematica, vol. 35 no. 1 (January, 2010), pp. 131-174, Finnish Academy of Science and Letters, ISSN 1239-629X [0709.1975v4], [doi]  [abs]
  50. Chen, G; Maggioni, M, Multiscale geometric wavelets for the analysis of point clouds, 2010 44th Annual Conference on Information Sciences and Systems, Ciss 2010 (February, 2010), IEEE [doi]  [abs]
  51. Wu, Q; Guinney, J; Maggioni, M; Mukherjee, S, Learning gradients: Predictive models that infer geometry and statistical dependence, Journal of Machine Learning Research, vol. 11 (August, 2010), pp. 2175-2198, ISSN 1532-4435 [repository]  [abs]
  52. Willinger, W; Rejaie, R; Torkjazi, M; Valafar, M; Maggioni, M, Research on online social networks: Time to face the real challenges, Acm Sigmetrics Performance Evaluation Review, vol. 37 no. 3 (August, 2010), pp. 49-54, Association for Computing Machinery (ACM), ISSN 0163-5999 [doi]  [abs]
  53. Monson, EE; Chen, G; Brady, R; Maggioni, M, Data representation and exploration with Geometric Wavelets, 2010 Ieee Symposium on Visual Analytics Science and Technology (October, 2010), pp. 243-244, IEEE [doi]  [abs]
  54. Allard, WK; Chen, G; Maggioni, M, Multiscale Geometric Methods for Data Sets II: Geometric Wavelets, CoRR, vol. abs/1105.4924 no. 3 (2012)
  55. G. Chen, M. Maggioni, Multiscale Geometric Dictionaries for point-cloud data, Proc. SampTA 2011 (2011)
  56. G. Chen, M. Maggioni, Multiscale Analysis of Plane Arrangements, in Proc. C.V.P.R. (2011)
  57. Chen, G; Maggioni, M, Multiscale geometric and spectral analysis of plane arrangements, Proceedings of the Ieee Computer Society Conference on Computer Vision and Pattern Recognition (January, 2011), pp. 2825-2832, IEEE, ISSN 1063-6919 [doi]  [abs]
  58. Chen, G; Little, AV; Maggioni, M; Rosasco, L, Some recent advances in multiscale geometric analysis of point clouds, in Applied and Numerical Harmonic Analysis (January, 2011), pp. 199-225, Birkhäuser Boston, ISBN 9780817680947 [doi]  [abs]
  59. Rohrdanz, MA; Zheng, W; Maggioni, M; Clementi, C, Determination of reaction coordinates via locally scaled diffusion map., The Journal of Chemical Physics, vol. 134 no. 12 (2011), pp. 124116 [21456654], [doi]  [abs]
  60. G. Chen, A.V. Little, M. Maggioni, L. Rosasco, Some recent advances in multiscale geometric analysis of point clouds, in Wavelets and Multiscale Analysis: Theory and Applications (March, 2011), Springer
  61. Zheng, W; Rohrdanz, MA; Maggioni, M; Clementi, C, Polymer reversal rate calculated via locally scaled diffusion map., The Journal of Chemical Physics, vol. 134 no. 14 (2011), pp. 144109 [21495744], [doi]  [abs]
  62. Maggioni, M, What is...data mining?, A.M.S. Notices (April, 2012) [pdf]
  63. Iwen, MA; Maggioni, M, Approximation of Points on Low-Dimensional Manifolds Via Random Linear Projections, vol. 2 (February, 2013) [1204.3337v1], [doi]  [abs]
  64. Allard, WK; Chen, G; Maggioni, M, Multi-scale geometric methods for data sets II: Geometric Multi-Resolution Analysis, Applied and Computational Harmonic Analysis, vol. 32 no. 3 (May, 2012), pp. 435-462, Elsevier BV, ISSN 1063-5203 [doi]  [abs]
  65. Bouvrie, J; Maggioni, M, Efficient solution of Markov decision problems with multiscale representations, 2012 50th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2012 (December, 2012), pp. 474-481, IEEE [doi]  [abs]
  66. Bouvrie, J; Maggioni, M, Geometric multiscale reduction for autonomous and controlled nonlinear systems, in Proc. IEEE Conference on Decision and Control (CDC), Proceedings of the Ieee Conference on Decision and Control (December, 2012), pp. 4320-4327, IEEE, ISBN 9781467320658 [mostRecentIssue.jsp], [doi]  [abs]
  67. Chen, G; Iwen, M; Chin, S; Maggioni, M, A fast multiscale framework for data in high-dimensions: Measure estimation, anomaly detection, and compressive measurements, 2012 Ieee Visual Communications and Image Processing, Vcip 2012 (December, 2012), pp. 1-6, IEEE, ISBN 9781467344050 [mostRecentIssue.jsp], [doi]  [abs]
  68. Maggioni, M, Geometric estimation of probability measures in high-dimensions, Conference Record Asilomar Conference on Signals, Systems and Computers (January, 2013), pp. 1363-1367, IEEE, ISSN 1058-6393 [doi]  [abs]
  69. Krishnamurthy, K; Mrozack, A; Maggioni, M; Brady, D, Multiscale, dictionary-based speckle denoising, in Proc. Computational Optical Sensing and Imaging, Optics Infobase Conference Papers (January, 2013), ISBN 978-1-55752-975-6 [doi]  [abs]
  70. Chen, G; Little, AV; Maggioni, M, Multi-resolution geometric analysis for data in high dimensions, in Applied and Numerical Harmonic Analysis, vol. 1 (January, 2013), pp. 259-285, Birkhäuser Boston, ISBN 9780817683757 [doi]  [abs]
  71. Coppola, A; Wenner, BR; Ilkayeva, O; Stevens, RD; Maggioni, M; Slotkin, TA; Levin, ED; Newgard, CB, Branched-chain amino acids alter neurobehavioral function in rats., American journal of physiology. Endocrinology and metabolism, vol. 304 no. 4 (February, 2013), pp. E405-E413 [23249694], [doi]  [abs]
  72. M. Maggioni, Geometric Estimation of Probability Measures in High-Dimensions, Proc. IEEE Asilomar Conference (November, 2013)
  73. Gerber, S; Maggioni, M, Multiscale dictionaries, transforms, and learning in high-dimensions, Smart Structures and Materials 2005: Active Materials: Behavior and Mechanics, vol. 8858 (December, 2013), SPIE, ISSN 0277-786X, ISBN 9780819497086 [Gateway.cgi], [doi]  [abs]
  74. Altemose, N; Miga, KH; Maggioni, M; Willard, HF, Genomic characterization of large heterochromatic gaps in the human genome assembly., Plos Computational Biology, vol. 10 no. 5 (May, 2014), pp. e1003628, ISSN 1553-734X [doi]  [abs]
  75. M. Maggioni, S. Minsker, N. Strawn, Multiscale Dictionary and Manifold Learning: Non-Asymptotic Bounds for the Geometric Multi-Resolution Analysis, in Proc. iTWIST’14: international - Traveling Workshop on Interactions between Sparse models and Technology (August, 2014)
  76. Maggioni, M, Geometry of data and biology, Notices of the American Mathematical Society, vol. 62 no. 10 (January, 2015), pp. 1185-1188, American Mathematical Society (AMS), ISSN 0002-9920 [doi]
  77. Maggioni, M; Minsker, S; Strawn, N, Geometric multi-resolution analysis for dictionary learning, Smart Structures and Materials 2005: Active Materials: Behavior and Mechanics, vol. 9597 (January, 2015), SPIE, ISSN 0277-786X, ISBN 9781628417630 [doi]  [abs]
  78. Goetzmann, WN; Jones, PW; Maggioni, M; Walden, J, Beauty is in the bid of the beholder: An empirical basis for style, Research in Economics, vol. 70 no. 3 (September, 2016), pp. 388-402, Elsevier BV [doi]  [abs]
  79. Liao, W; Maggioni, M; Vigogna, S, Learning adaptive multiscale approximations to data and functions near low-dimensional sets, 2016 Ieee Information Theory Workshop, Itw 2016 (October, 2016), pp. 226-230, IEEE, ISBN 9781509010905 [doi]  [abs]
  80. Tomita, TM; Maggioni, M; Vogelstein, JT, ROFLMAO: Robust oblique forests with linear MAtrix operations, Proceedings of the 17th Siam International Conference on Data Mining, Sdm 2017 (January, 2017), pp. 498-506, ISBN 9781611974874  [abs]
  81. Crosskey, M; Maggioni, M, ATLAS: A geometric approach to learning high-dimensional stochastic systems near manifolds, Multiscale Modeling & Simulation, vol. 15 no. 1 (January, 2017), pp. 110-156, Society for Industrial & Applied Mathematics (SIAM) [doi]  [abs]
  82. Bongini, M; Fornasier, M; Hansen, M; Maggioni, M, Inferring interaction rules from observations of evolutive systems I: The variational approach, Mathematical Models and Methods in Applied Sciences, vol. 27 no. 5 (May, 2017), pp. 909-951, World Scientific Pub Co Pte Lt [doi]  [abs]
  83. Gerber, S; Maggioni, M, Multiscale strategies for computing optimal transport, Journal of Machine Learning Research, vol. 18 (August, 2017), pp. 1-32  [abs]
  84. Wang, YG; Maggioni, M; Chen, G, Enhanced detection of chemical plumes in hyperspectral images and movies throughimproved backgroundmodeling, Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing, vol. 2015-June (October, 2017), IEEE, ISBN 9781467390156 [doi]  [abs]
  85. Little, AV; Maggioni, M; Rosasco, L, Multiscale geometric methods for data sets I: Multiscale SVD, noise and curvature, Applied and Computational Harmonic Analysis, vol. 43 no. 3 (November, 2017), pp. 504-567, Elsevier BV [doi]  [abs]
  86. Escande, P; Debarnot, V; Maggioni, M; Mangeat, T; Weiss, P, Learning and exploiting physics of degradations, Optics Infobase Conference Papers, vol. Part F105-MATH 2018 (January, 2018), OSA, ISBN 9781557528209 [doi]  [abs]
  87. Murphy, JM; Maggioni, M, Diffusion geometric methods for fusion of remotely sensed data, Smart Structures and Materials 2005: Active Materials: Behavior and Mechanics, vol. 10644 (January, 2018), SPIE, ISBN 9781510617995 [doi]  [abs]
  88. Vogelstein, JT; Bridgeford, EW; Wang, Q; Priebe, CE; Maggioni, M; Shen, C, Discovering and deciphering relationships across disparate data modalities., Elife, vol. 8 (January, 2019) [doi]  [abs]
  89. Murphy, JM; Maggioni, M, Unsupervised Clustering and Active Learning of Hyperspectral Images with Nonlinear Diffusion, Ieee Transactions on Geoscience and Remote Sensing, vol. 57 no. 3 (March, 2019), pp. 1829-1845, Institute of Electrical and Electronics Engineers (IEEE) [doi]  [abs]

Papers Accepted

  1. A.V. Little, M. Maggioni, L. Rosasco, Multiscale Geometric Methods for Data Sets I: Multiscale SVD, Noise and Curvature (2012)
  2. M. Crosskey, M. Maggioni, ATLAS: A geometric approach to learning high-dimensional stochastic systems near manifolds, SIAM Journ. Mult. Model. Simul. (2015)
  3. Maggioni, M; Minsker, S; Strawn, N, Multiscale dictionary learning: Non-asymptotic bounds and robustness, Journal of Machine Learning Research, vol. 17 (January, 2016), ISSN 1532-4435 (accepted for publication.) [arxiv:1401.5833]  [abs]
  4. Yin, R; Monson, E; Honig, E; Daubechies, I; Maggioni, M, Object recognition in art drawings: Transfer of a neural network, 2015 Ieee International Conference on Acoustics, Speech, and Signal Processing (Icassp), vol. 2016-May (May, 2016), pp. 2299-2303, IEEE, ISSN 1520-6149, ISBN 9781479999880 [doi]  [abs]

Papers Submitted

  1. William Goetzmann and Peter W Jones and Mauro Maggioni and Johan Walden, Beauty is in the eye of the beholder, submitted (2004)
  2. Mauro Maggioni and Ronald R Coifman, Multiscale Spectral Analysis on Data Sets with Diffusion Wavelets, in submitted (2006)
  3. Mauro Maggioni and Sridhar Mahadevan, Multiscale Diffusion Bases for Policy Iteration in Markov Decision Processes, submitted (2006)
  4. J. Bouvrie, M. Maggioni, Multiscale Markov Decision Problems: Compression, Solution, and Transfer Learning (2012) [1212.1143]
  5. M. Crosskey, M. Maggioni, ATLAS: A geometric approach to learning high-dimensional stochastic systems near manifolds (2014) [arXiv:1404.0667]
  6. T. Tomita, J. Vogelstein, M. Maggioni, Randomer Forests (2015)
  7. Wang, Y; Chen, G; Maggioni, M, High-Dimensional Data Modeling Techniques for Detection of Chemical Plumes and Anomalies in Hyperspectral Images and Movies, Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 9 no. 9 (September, 2016), pp. 4316-4324, Institute of Electrical and Electronics Engineers (IEEE), ISSN 1939-1404 [doi]  [abs]

Preprints

  1. GL Davis and Mauro Maggioni and FJ Warner and FB Geshwind and AC Coppi and RA DeVerse and RR Coifman, Hyper-spectral Analysis of normal and malignant colon tissue microarray sections using a novel DMD system (2004) (Poster, Optical Imaging NIH workshop, to app. in proc..)
  2. Ronald R Coifman and Mauro Maggioni, Multiresolution Analysis associated to diffusion semigroups: construction and fast algorithms no. YALE/DCS/TR-1289 (2004)
  3. Ronald Raphel Coifman and Mauro Maggioni, Multiscale Analysis of Document Corpora (2006)

Other

  1. RR Coifman, A. Coppi, F. Geshwind, SS Lafon, AB Lee, M Maggioni, FJ Warner, SW Zucker, WG Fately, System and method for document analysis, processing and information extraction, U.S. Patent US2006/0004753A1 (January, 2006)
  2. M. Maggioni, R Coifman, AC Coppi, GL Davis, RA DeVerse, WG Fately, F. Geshwind, FJ Warner, System and method for hyperspectral analysis, US Patent US2006/0074835 A1 (April, 2006)
  3. E. Liberty, S. Zucker, Y. Keller, M. Maggioni, R.R. Coifman, F. Geshwind, Methods for filtering data and filling in missing data using nonlinear filtering, US Patent US2006/0214133 A1 (April, 2007)
Duke University * Arts & Sciences * Mathematics * April 19, 2024

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