Abstract:
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We present a formal result on optimality of the L_0 penalty for variable selection in terms of the under-fitting and over-fitting probabilities. It is used to obtain a precise understanding on dual achievability of model selection, i.e., if and when we can achieve both model selection consistency and minimax rate estimation of the regression function in strong and weak senses. The work is joint with Zhan Wang.
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