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    IGARSS
    2010
    162views Remote Sensing» more  IGARSS 2010»
    Support vector machines regression for estimation of forest parameters from airborne laser scanning data
    13 years 6 months ago
    Support vector machines regression for estimation of forest parameters from airborne laser scanning data
    Download  hal.archives-ouvertes.fr
    Estimation of forest stand parameters from airborne laser scanning data relies on the selection of laser metrics sets and numerous field plots for model calibration. In mountainou...
    Jean-Matthieu Monnet, Frédéric Berge...
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    KDD
    2004
    ACM
    132views Data Mining» more  KDD 2004»
    Privacy preserving regression modelling via distributed computation
    14 years 8 months ago
    Privacy preserving regression modelling via distributed computation
    Download  math.uc.edu
    Reluctance of data owners to share their possibly confidential or proprietary data with others who own related databases is a serious impediment to conducting a mutually beneficia...
    Ashish P. Sanil, Alan F. Karr, Xiaodong Lin, Jerom...
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    ICDM
    2008
    IEEE
    182views Data Mining» more  ICDM 2008»
    Multiple-Instance Regression with Structured Data
    14 years 2 months ago
    Multiple-Instance Regression with Structured Data
    Download  ml.jpl.nasa.gov
    We present a multiple-instance regression algorithm that models internal bag structure to identify the items most relevant to the bag labels. Multiple-instance regression (MIR) op...
    Kiri L. Wagstaff, Terran Lane, Alex Roper
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    SDM
    2011
    SIAM
    233views Data Mining» more  SDM 2011»
    Distributed Monitoring of the R2 Statistic for Linear Regression
    12 years 11 months ago
    Distributed Monitoring of the R2 Statistic for Linear Regression
    Download  www.cs.umbc.edu
    The problem of monitoring a multivariate linear regression model is relevant in studying the evolving relationship between a set of input variables (features) and one or more depe...
    Kanishka Bhaduri, Kamalika Das, Chris Giannella
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    JMLR
    2006
    87views more  JMLR 2006»
    Second Order Cone Programming Approaches for Handling Missing and Uncertain Data
    13 years 8 months ago
    Second Order Cone Programming Approaches for Handling Missing and Uncertain Data
    Download  jmlr.csail.mit.edu
    We propose a novel second order cone programming formulation for designing robust classifiers which can handle uncertainty in observations. Similar formulations are also derived f...
    Pannagadatta K. Shivaswamy, Chiranjib Bhattacharyy...
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