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    DAC
    2004
    ACM
    171views Computer Architecture» more  DAC 2004»
    SUNMAP: a tool for automatic topology selection and generation for NoCs
    16 years 8 months ago
    SUNMAP: a tool for automatic topology selection and generation for NoCs
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    Srinivasan Murali, Giovanni De Micheli
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    DAC
    2006
    ACM
    105views Computer Architecture» more  DAC 2006»
    A fast simultaneous input vector generation and gate replacement algorithm for leakage power reduction
    16 years 8 months ago
    A fast simultaneous input vector generation and gate replacement algorithm for leakage power reduction
    Download  icims.csl.uiuc.edu
    Lei Cheng, Liang Deng, Deming Chen, Martin D. F. W...
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    MICCAI
    2002
    Springer
    129views Medical Imaging» more  MICCAI 2002»
    Automatic Generation of Training Data for Brain Tissue Classification from MRI
    16 years 8 months ago
    Automatic Generation of Training Data for Brain Tissue Classification from MRI
    Download  www.bic.mni.mcgill.ca
    Chris A. Cocosco, Alex P. Zijdenbos, Alan C. Evans
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    ICML
    2007
    IEEE
    106views Machine Learning» more  ICML 2007»
    Linear and nonlinear generative probabilistic class models for shape contours
    16 years 8 months ago
    Linear and nonlinear generative probabilistic class models for shape contours
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    We introduce a robust probabilistic approach to modeling shape contours based on a lowdimensional, nonlinear latent variable model. In contrast to existing techniques that use obj...
    Graham McNeill, Sethu Vijayakumar
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    ICML
    2008
    IEEE
    171views Machine Learning» more  ICML 2008»
    An asymptotic analysis of generative, discriminative, and pseudolikelihood estimators
    16 years 8 months ago
    An asymptotic analysis of generative, discriminative, and pseudolikelihood estimators
    Download  www.cs.berkeley.edu
    Statistical and computational concerns have motivated parameter estimators based on various forms of likelihood, e.g., joint, conditional, and pseudolikelihood. In this paper, we ...
    Percy Liang, Michael I. Jordan
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