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    ICDM
    2005
    IEEE
    138views Data Mining» more  ICDM 2005»
    Labeling Unclustered Categorical Data into Clusters Based on the Important Attribute Values
    13 years 12 months ago
    Labeling Unclustered Categorical Data into Clusters Based on the Important Attribute Values
    Download  arbor.ee.ntu.edu.tw
    Sampling has been recognized as an important technique to improve the efficiency of clustering. However, with sampling applied, those points which are not sampled will not have t...
    Hung-Leng Chen, Kun-Ta Chuang, Ming-Syan Chen
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    3DPH
    2009
    128views Healthcare» more  3DPH 2009»
    Predicting Missing Markers in Real-Time Optical Motion Capture
    13 years 7 months ago
    Predicting Missing Markers in Real-Time Optical Motion Capture
    Download  www.t2i.se
    Abstract. A common problem in optical motion capture of human-body movement is the so-called missing marker problem. The occlusion of markers can lead to significant problems in tr...
    Tommaso Piazza, Johan Lundström, Andreas Kunz...
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    NECO
    1998
    121views more  NECO 1998»
    Nonlinear Time-Series Prediction with Missing and Noisy Data
    13 years 5 months ago
    Nonlinear Time-Series Prediction with Missing and Noisy Data
    Download  wwwbrauer.in.tum.de
    We derive solutions for the problem of missing and noisy data in nonlinear timeseries prediction from a probabilistic point of view. We discuss different approximations to the so...
    Volker Tresp, Reimar Hofmann
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    CVPR
    1996
    IEEE
    155views Computer Vision» more  CVPR 1996»
    Determining Correspondences and Rigid Motion of 3-D Point Sets with Missing Data
    14 years 8 months ago
    Determining Correspondences and Rigid Motion of 3-D Point Sets with Missing Data
    Download  www.ri.cmu.edu
    This paper addresses the general 3-D rigid motion problem, where the point correspondences and the motion parameters between two sets of 3-D points are to be recovered. The existe...
    Xiaoguang Wang, Yong-Qing Cheng, Robert T. Collins...
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    ICCV
    2009
    IEEE
    792views Computer Vision» more  ICCV 2009»
    Tensor completion for estimating missing values in visual data
    14 years 11 months ago
    Tensor completion for estimating missing values in visual data
    Download  www.public.asu.edu
    In this paper we propose an algorithm to estimate missing values in tensors of visual data. The values can be missing due to problems in the acquisition process, or because the ...
    Ji Liu, Przemyslaw Musialski, Peter Wonka, Jieping...
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