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    NIPS
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    On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization
    14 years 29 days ago
    On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization
    Download  ttic.uchicago.edu
    This work characterizes the generalization ability of algorithms whose predictions are linear in the input vector. To this end, we provide sharp bounds for Rademacher and Gaussian...
    Sham M. Kakade, Karthik Sridharan, Ambuj Tewari
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