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    JMLR
    2008
    132views more  JMLR 2008»
    Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data
    13 years 3 months ago
    Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data
    Download  www.eecs.berkeley.edu
    Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...
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    CORR
    2007
    Springer
    128views Education» more  CORR 2007»
    Model Selection Through Sparse Maximum Likelihood Estimation
    13 years 4 months ago
    Model Selection Through Sparse Maximum Likelihood Estimation
    Download  www.princeton.edu
    We consider the problem of estimating the parameters of a Gaussian or binary distribution in such a way that the resulting undirected graphical model is sparse. Our approach is to...
    Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...
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    ICML
    2006
    IEEE
    194views Machine Learning» more  ICML 2006»
    Convex optimization techniques for fitting sparse Gaussian graphical models
    14 years 5 months ago
    Convex optimization techniques for fitting sparse Gaussian graphical models
    Download  www.eecs.berkeley.edu
    We consider the problem of fitting a large-scale covariance matrix to multivariate Gaussian data in such a way that the inverse is sparse, thus providing model selection. Beginnin...
    Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...
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    SDM
    2009
    SIAM
    202views Data Mining» more  SDM 2009»
    Proximity-Based Anomaly Detection Using Sparse Structure Learning.
    14 years 1 months ago
    Proximity-Based Anomaly Detection Using Sparse Structure Learning.
    Download  www.research.ibm.com
    We consider the task of performing anomaly detection in highly noisy multivariate data. In many applications involving real-valued time-series data, such as physical sensor data a...
    Tsuyoshi Idé, Aurelie C. Lozano, Naoki Abe,...
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    SADM
    2010
    141views more  SADM 2010»
    A parametric mixture model for clustering multivariate binary data
    12 years 11 months ago
    A parametric mixture model for clustering multivariate binary data
    Download  users.iems.northwestern.edu
    : The traditional latent class analysis (LCA) uses a mixture model with binary responses on each subject that are independent conditional on cluster membership. However, in many pr...
    Ajit C. Tamhane, Dingxi Qiu, Bruce E. Ankenman
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