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    TSP
    2012
    344views Artificial Intelligence» more  TSP 2012»
    Distributed Covariance Estimation in Gaussian Graphical Models
    12 years 4 months ago
    Distributed Covariance Estimation in Gaussian Graphical Models
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    —We consider distributed estimation of the inverse covariance matrix in Gaussian graphical models. These models factorize the multivariate distribution and allow for efficient d...
    Ami Wiesel, Alfred O. Hero
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    TIT
    2010
    118views Education» more  TIT 2010»
    Joint sampling distribution between actual and estimated classification errors for linear discriminant analysis
    13 years 4 months ago
    Joint sampling distribution between actual and estimated classification errors for linear discriminant analysis
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    Error estimation must be used to find the accuracy of a designed classifier, an issue that is critical in biomarker discovery for disease diagnosis and prognosis in genomics and p...
    Amin Zollanvari, Ulisses Braga-Neto, Edward R. Dou...
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    CVPR
    1999
    IEEE
    135views Computer Vision» more  CVPR 1999»
    Optimal Rigid Motion Estimation and Performance Evaluation with Bootstrap
    14 years 11 months ago
    Optimal Rigid Motion Estimation and Performance Evaluation with Bootstrap
    Download  www.caip.rutgers.edu
    A new method for 3D rigid motion estimation is derived under the most general assumption that the measurements are corrupted by inhomogeneous and anisotropic, i.e., heteroscedasti...
    Bogdan Matei, Peter Meer
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    CVPR
    2005
    IEEE
    236views Computer Vision» more  CVPR 2005»
    A Bayesian Approach to Unsupervised Feature Selection and Density Estimation Using Expectation Propagation
    14 years 11 months ago
    A Bayesian Approach to Unsupervised Feature Selection and Density Estimation Using Expectation Propagation
    Download  people.ee.duke.edu
    We propose an approximate Bayesian approach for unsupervised feature selection and density estimation, where the importance of the features for clustering is used as the measure f...
    Shaorong Chang, Nilanjan Dasgupta, Lawrence Carin
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    CVPR
    2008
    IEEE
    197views Computer Vision» more  CVPR 2008»
    On errors-in-variables regression with arbitrary covariance and its application to optical flow estimation
    14 years 11 months ago
    On errors-in-variables regression with arbitrary covariance and its application to optical flow estimation
    Download  hci.iwr.uni-heidelberg.de
    Linear inverse problems in computer vision, including motion estimation, shape fitting and image reconstruction, give rise to parameter estimation problems with highly correlated ...
    Björn Andres, Claudia Kondermann, Daniel Kond...
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