Computable Bayesian compression for uniformly discretizable statistical models
ALT'09 Proceedings of the 20th international conference on Algorithmic learning theory
Asymptotic log-loss of prequential maximum likelihood codes
COLT'05 Proceedings of the 18th annual conference on Learning Theory
| Hi-index | 754.84 |
Rissanen's (1978, 1986, 1989, 1996) minimum description length (MDL) principle is a statistical modeling principle motivated by coding theory. For exponential families we obtain pathwise expansions, to the constant order, of the predictive and mixture codelengths used in MDL. The results are useful for understanding different MDL forms