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About this paper
Peter Grünwald, Teemu Roos
The authors review post-2007 developments in minimum description length (MDL), a framework for choosing models through predictive distributions. The review connects this approach to penalized-likelihood and Bayesian methods, and surveys applications to estimation, prediction, and testing. A switch-based procedure is reported to be strongly consistent with order-log-log-n cumulative log-loss overhead, under stated conditions; it does not eliminate every prediction-consistency tradeoff.
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