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    KDD
    2006
    ACM
    170views Data Mining» more  KDD 2006»
    Computer aided detection via asymmetric cascade of sparse hyperplane classifiers
    14 years 7 months ago
    Computer aided detection via asymmetric cascade of sparse hyperplane classifiers
    Download  pages.cs.wisc.edu
    This paper describes a novel classification method for computer aided detection (CAD) that identifies structures of interest from medical images. CAD problems are challenging larg...
    Jinbo Bi, Senthil Periaswamy, Kazunori Okada, Tosh...
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    JMLR
    2010
    159views more  JMLR 2010»
    Inference of Sparse Networks with Unobserved Variables. Application to Gene Regulatory Networks
    13 years 1 months ago
    Inference of Sparse Networks with Unobserved Variables. Application to Gene Regulatory Networks
    Download  www.princeton.edu
    Networks are becoming a unifying framework for modeling complex systems and network inference problems are frequently encountered in many fields. Here, I develop and apply a gener...
    Nikolai Slavov
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    ICDE
    2005
    IEEE
    102views Database» more  ICDE 2005»
    Modeling and Managing Content Changes in Text Databases
    14 years 8 months ago
    Modeling and Managing Content Changes in Text Databases
    Download  pages.stern.nyu.edu
    Large amounts of (often valuable) information are stored in web-accessible text databases. "Metasearchers" provide unified interfaces to query multiple such databases at...
    Panagiotis G. Ipeirotis, Alexandros Ntoulas, Jungh...
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    PRL
    2010
    149views more  PRL 2010»
    Adaptive linear models for regression: Improving prediction when population has changed
    13 years 1 months ago
    Adaptive linear models for regression: Improving prediction when population has changed
    Download  hal.archives-ouvertes.fr
    The general setting of regression analysis is to identify a relationship between a response variable Y and one or several explanatory variables X by using a learning sample. In a ...
    Charles Bouveyron, Julien Jacques
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    ICML
    2005
    IEEE
    195views Machine Learning» more  ICML 2005»
    Active learning for Hidden Markov Models: objective functions and algorithms
    14 years 7 months ago
    Active learning for Hidden Markov Models: objective functions and algorithms
    Download  www.cs.cmu.edu
    Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...
    Brigham Anderson, Andrew Moore
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