IEEE Organizations related to Nonparametric Statistics

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No organizations are currently tagged "Nonparametric Statistics"



Conferences related to Nonparametric Statistics

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2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI 2020)

The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2020 will be the 17th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2020 meeting will continue this tradition of fostering cross-fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging.ISBI 2019 will be the 16th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2019 meeting will continue this tradition of fostering cross fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2018 will be the 15th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2018 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2017 will be the 14th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2017 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI 2016)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forumfor the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2016 willbe the thirteenth meeting in this series. The previous meetings have played a leading role in facilitatinginteraction between researchers in medical and biological imaging. The 2016 meeting will continue thistradition of fostering crossfertilization among different imaging communities and contributing to an integrativeapproach to biomedical imaging across all scales of observation.

  • 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI 2015)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2015 will be the 12th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2014 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI 2014)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2014 will be the eleventh meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2014 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI 2013)

    To serve the biological, biomedical, bioengineering, bioimaging and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2012 IEEE 9th International Symposium on Biomedical Imaging (ISBI 2012)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2011 IEEE 8th International Symposium on Biomedical Imaging (ISBI 2011)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2010 IEEE 7th International Symposium on Biomedical Imaging (ISBI 2010)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2009 IEEE 6th International Symposium on Biomedical Imaging (ISBI 2009)

    Algorithmic, mathematical and computational aspects of biomedical imaging, from nano- to macroscale. Topics of interest include image formation and reconstruction, computational and statistical image processing and analysis, dynamic imaging, visualization, image quality assessment, and physical, biological and statistical modeling. Molecular, cellular, anatomical and functional imaging modalities and applications.

  • 2008 IEEE 5th International Symposium on Biomedical Imaging (ISBI 2008)

    Algorithmic, mathematical and computational aspects of biomedical imaging, from nano- to macroscale. Topics of interest include image formation and reconstruction, computational and statistical image processing and analysis, dynamic imaging, visualization, image quality assessment, and physical, biological and statistical modeling. Molecular, cellular, anatomical and functional imaging modalities and applications.

  • 2007 IEEE 4th International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2007)

  • 2006 IEEE 3rd International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2006)

  • 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2004)

  • 2002 1st IEEE International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2002)


2020 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and severalco-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students, academics and industry researchers.

  • 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conferenceand 27co-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students,academics and industry.

  • 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    computer, vision, pattern, cvpr, machine, learning

  • 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. Main conference plus 50 workshop only attendees and approximately 50 exhibitors and volunteers.

  • 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Topics of interest include all aspects of computer vision and pattern recognition including motion and tracking,stereo, object recognition, object detection, color detection plus many more

  • 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Sensors Early and Biologically-Biologically-inspired Vision, Color and Texture, Segmentation and Grouping, Computational Photography and Video

  • 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics, motion analysis and physics-based vision.

  • 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics,motion analysis and physics-based vision.

  • 2008 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2007 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2006 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2005 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)


2020 IEEE International Conference on Consumer Electronics (ICCE)

The International Conference on Consumer Electronics (ICCE) is soliciting technical papersfor oral and poster presentation at ICCE 2018. ICCE has a strong conference history coupledwith a tradition of attracting leading authors and delegates from around the world.Papers reporting new developments in all areas of consumer electronics are invited. Topics around the major theme will be the content ofspecial sessions and tutorials.


2020 IEEE International Conference on Image Processing (ICIP)

The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2020, the 27th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.


2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)

The Conference focuses on all aspects of instrumentation and measurement science andtechnology research development and applications. The list of program topics includes but isnot limited to: Measurement Science & Education, Measurement Systems, Measurement DataAcquisition, Measurements of Physical Quantities, and Measurement Applications.


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Periodicals related to Nonparametric Statistics

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No periodicals are currently tagged "Nonparametric Statistics"


Most published Xplore authors for Nonparametric Statistics

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Xplore Articles related to Nonparametric Statistics

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Synthesis and the Analysis of the Nonparametric Systems of a Pattern Recognition Based on Decomposition on Dimension of the Training Selection

2018 International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon), 2018

From positions of the principles of training selection decomposition and collective estimation the synthesis technique of multilevel nonparametric systems of pattern recognition for the multialternate classification problem is offered. Their application provides high computing performance of information processing of big dimension. Two approaches are considered. Poorly dependent feature sets of the classified objects are in case of the former used. ...


Application of the Principle of Analytic Continuation to Interpolate/Extrapolate System Responses Resulting in Reduced Computations—Part B: Nonparametric Methods

IEEE Journal on Multiscale and Multiphysics Computational Techniques, 2016

This review paper is a sequel to our earlier paper entitled “Application of the principle of analytic continuation to interpolate/extrapolate system responses resulting in reduced computations-Part A: Parametric methods” dealing with parametric methods in the context of the principle of analytic continu-ation and providing its relationship to reduced rank modeling using the total least-squares-based singular value decomposition methodology. The problem ...


An Efficient Framework for Detecting Evolving Anomalous Subgraphs in Dynamic Networks

IEEE INFOCOM 2018 - IEEE Conference on Computer Communications, 2018

Evolving anomalous subgraphs detection in dynamic networks is an important and challenging problem that has arisen in multiple applications and is NP-hard in general. The evolving characteristic makes most existing methods incapable to tackle this problem effectively and efficiently, as it involves huge search spaces and continuous changes of evolving connected subgraphs, especially when the data are free of distributions. ...



Educational Resources on Nonparametric Statistics

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IEEE.tv Videos

Applied Nonparametric hierarchical Bayes
Broadening Participation in Computing and Empowering Female Leaders with Maria Klawe - IEEE WIE ILC 2017
Technical Program Overview - Antonio Skarmeta - 5G World Forum Santa Clara 2018
Cathy Chen from Exponent at WIE ILC 2016
Dictionary Learning: Principles, Algorithms, Guarantees
Louis Scharf receives the IEEE Jack S. Kilby Signal Processing Medal - Honors Ceremony 2016
Plotting the Course for Nationwide 5G Deployment - Egil Gronstad - 5G World Forum Santa Clara 2018
The European Startup Scene - Jose Pozo - IPC 2018
Internet of Things Panelist - Clint Andrews: 2016 Technology Time Machine
Operator Keynote: Andre Fuetsch - B5GS 2019
IEEEXtreme: IEEE’s Largest Programming Competition - Prasanth Mohan - Ignite: Sections Congress 2017
IEEE Women In Engineering - Bozenna Pasik-Duncan - Ignite: Sections Congress 2017
IEEE's Leah Jamieson focuses on Women Accelerating Change through Philanthropy - 2016 Women in Engineering Conference
Building the Bridge to the Future - Mary Ellen Randall - Opening Ceremony: Sections Congress 2017
Netflix's Chris Pouliot: How to Build a Data Science Team from Scratch
A Bayesian Approach for Spatial Clustering - IEEE CIS Webinar
New value creation with the Future X Network - Peter Vetter - IEEE Sarnoff Symposium, 2019
2015 IEEE Honors: IEEE Richard W. Hamming Medal - Imre Csiszar
IEEE Internet Initiative - Mission and Goals; Review of Previous ETAP Forums; Goals for ETAP Namibia: Maike Luiken - ETAP Forum Namibia, Africa 2017
IMS 2014: Wideband mmWave Channels: Implications for Design and Implementation of Adaptive Beam Antennas

IEEE-USA E-Books

  • Synthesis and the Analysis of the Nonparametric Systems of a Pattern Recognition Based on Decomposition on Dimension of the Training Selection

    From positions of the principles of training selection decomposition and collective estimation the synthesis technique of multilevel nonparametric systems of pattern recognition for the multialternate classification problem is offered. Their application provides high computing performance of information processing of big dimension. Two approaches are considered. Poorly dependent feature sets of the classified objects are in case of the former used. Considering the assumption of independence of feature sets the generalized decisive rule of maximum likelihood is under construction. The basis of the second method is made by a dichotomy method. At each its stage we form the family of the private decision functions corresponding to various feature sets of the classified objects with the subsequent their integration in the non-linear decisive rule by means of methods of nonparametric statistics. At the same time formation of the generalized decision on situation belonging to this or that class is carried out in space of values of private decision functions. The offered technique allows to use technology of parallel calculations.

  • Application of the Principle of Analytic Continuation to Interpolate/Extrapolate System Responses Resulting in Reduced Computations—Part B: Nonparametric Methods

    This review paper is a sequel to our earlier paper entitled “Application of the principle of analytic continuation to interpolate/extrapolate system responses resulting in reduced computations-Part A: Parametric methods” dealing with parametric methods in the context of the principle of analytic continu-ation and providing its relationship to reduced rank modeling using the total least-squares-based singular value decomposition methodology. The problem with a parametric method is that the quality of the solution is determined by the choice of the basis functions, and the use of bad basis functions generates bad solutions. A priori, it is quite difficult to recognize what are good basis functions and what are bad basis functions, even though methodologies exist in theory on how to choose good ones. The advantage of the nonparametric methods is that no such choices of the basis functions need to be made, as the solution procedure itself develops the nature of the solution and no a priori information is necessary. This is accomplished through the use of the Hilbert transform, which exploits one of the fundamental properties of nature, i.e., causality. The Hilbert transform illustrates that the real and imaginary parts of any nonminimum-phase transfer function from a causal system satisfy this relationship. In addition, some parameterization can also be made of this procedure, which can enable one to generate a nonminimum-phase function from its amplitude response and from that generate the phase response and, thereby, can compute the time-domain data for the amplitude-only case except for a delay in the response. This uncertainty is removed in holography, as in such a procedure, amplitude and phase information is measured for a specific look angle, thus eliminating the phase ambiguity. An overview of the technique along with examples is presented to illustrate this methodology.

  • An Efficient Framework for Detecting Evolving Anomalous Subgraphs in Dynamic Networks

    Evolving anomalous subgraphs detection in dynamic networks is an important and challenging problem that has arisen in multiple applications and is NP-hard in general. The evolving characteristic makes most existing methods incapable to tackle this problem effectively and efficiently, as it involves huge search spaces and continuous changes of evolving connected subgraphs, especially when the data are free of distributions. This paper presents a generic efficient framework, namely dynamic evolving anomalous subgraphs scanning (dGraphScan), to address this problem. We generalize traditional nonparametric scan statistics, and propose a large class of scan statistic functions for measuring the significance of evolving subgraphs in dynamic networks. Furthermore, we make a number of computational studies to optimize this large class of nonparametric scan statistic functions. Specifically, we first decompose each scan statistic function as a sequence of subproblems with provable guarantees, and then propose efficient approximation algorithms for tackling each subproblem, while analyzing their theoretical properties and providing rigorous approximation guarantees. Extensive experiments on three real-world datasets demonstrate that our general framework performs superior over state-of-the-art methods.



Standards related to Nonparametric Statistics

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No standards are currently tagged "Nonparametric Statistics"