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Model selection and sharp asymptotic minimaxity

Zhou, H (Yale)
Tuesday 29 January 2008, 11:00-12:30

Seminar Room 2, Newton Institute Gatehouse


We will show that a class of model selection procedures are asymptotically sharp minimax to recover sparse signals over a wide range of parameter spaces. Connections to Bayesian model selection, the MDL principle and wavelet estimation will be discussed.


[pdf ]

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