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    ESANN
    2000
    163views Neural Networks» more  ESANN 2000»
    Distributed clustering and local regression for knowledge discovery in multiple spatial databases
    13 years 9 months ago
    Distributed clustering and local regression for knowledge discovery in multiple spatial databases
    Download  www.ist.temple.edu
    Many large -scale spatial data analysis problems involve an investigation of relationships in heterogeneous databases. In such situations, instead of making predictions uniformly a...
    Aleksandar Lazarevic, Dragoljub Pokrajac, Zoran Ob...
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    ESWA
    2008
    204views more  ESWA 2008»
    A comparison of neural network and multiple regression analysis in modeling capital structure
    13 years 7 months ago
    A comparison of neural network and multiple regression analysis in modeling capital structure
    Download  www.engineering.wright.edu
    Empirical studies of the variation in debt ratios across firms have used statistical models singularly to analyze the important determinants of capital structure. Researchers, how...
    Hsiao-Tien Pao
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    PSIVT
    2009
    Springer
    139views Multimedia» more  PSIVT 2009»
    Recognizing Multiple Objects via Regression Incorporating the Co-occurrence of Categories
    14 years 2 months ago
    Recognizing Multiple Objects via Regression Incorporating the Co-occurrence of Categories
    Download  www.hci.iis.u-tokyo.ac.jp
    Abstract. Most previous methods for generic object recognition explicitly or implicitly assume that an image contains objects from a single category, although objects from multiple...
    Takahiro Okabe, Yuhi Kondo, Kris M. Kitani, Yoichi...
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    ICASSP
    2010
    IEEE
    145views Signal Processing» more  ICASSP 2010»
    Multiple frequency-hopping signal estimation via sparse regression
    13 years 7 months ago
    Multiple frequency-hopping signal estimation via sparse regression
    Download  www.tc.umn.edu
    Frequency hopping (FH) signals have well-documented merits for commercial and military applications due to their near-far resistance and robustness to jamming. Estimating FH signa...
    Daniele Angelosante, Georgios B. Giannakis, Nichol...
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    EOR
    2008
    99views more  EOR 2008»
    Ordinal regression revisited: Multiple criteria ranking using a set of additive value functions
    13 years 7 months ago
    Ordinal regression revisited: Multiple criteria ranking using a set of additive value functions
    Download  www.lamsade.dauphine.fr
    We present a new method, called UTAGMS , for multiple criteria ranking of alternatives from set A using a set of additive value functions which result from an ordinal regression. ...
    Salvatore Greco, Vincent Mousseau, Roman Slowinski
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