Empirical Bayes via ERM and Rademacher complexities: the Poisson model
We consider the problem of empirical Bayes estimation for (multivariate) Poisson means.
Existing solutions that have been shown theoretically optimal for minimizing the regret
(excess risk over the Bayesian oracle that knows the prior) have several shortcomings. For
example, the classical Robbins estimator does not retain the monotonicity property of the
Bayes estimator and performs poorly under moderate sample size. Estimators based on the
minimum distance and non-parametric maximum likelihood (NPMLE) methods correct these …
Existing solutions that have been shown theoretically optimal for minimizing the regret
(excess risk over the Bayesian oracle that knows the prior) have several shortcomings. For
example, the classical Robbins estimator does not retain the monotonicity property of the
Bayes estimator and performs poorly under moderate sample size. Estimators based on the
minimum distance and non-parametric maximum likelihood (NPMLE) methods correct these …
[BOOK][B] Empirical Bayes via ERM and Rademacher complexities: the Poisson model
AZY Teh - 2023 - search.proquest.com
We consider the problem of empirical Bayes estimation for (multivariate) Poisson means.
Existing solutions that have been shown theoretically optimal for minimizing the regret
(excess risk over the Bayesian oracle that knows the prior) have several shortcomings. For
example, the classical Robbins estimator does not retain the monotonicity property of the
Bayes estimator and performs poorly under moderate sample size. Estimators based on the
minimum distance and non-parametric maximum likelihood (NPMLE) methods correct these …
Existing solutions that have been shown theoretically optimal for minimizing the regret
(excess risk over the Bayesian oracle that knows the prior) have several shortcomings. For
example, the classical Robbins estimator does not retain the monotonicity property of the
Bayes estimator and performs poorly under moderate sample size. Estimators based on the
minimum distance and non-parametric maximum likelihood (NPMLE) methods correct these …
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