Penalized Maximum Likelihood Estimation Algorithm: Difference between revisions
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A [[Penalized Maximum Likelihood Estimation Algorithm]] is a [[Maximum Likelihood Estimation Algorithm]] that ... | A [[Penalized Maximum Likelihood Estimation Algorithm]] is a [[Maximum Likelihood Estimation Algorithm]] that ... | ||
** … | ** … | ||
* <B>Counter- | * <B>Counter-Example(s):</B> | ||
** an [[Unsmoothed Maximum Likelihood-based Training Algorithm]]. | ** an [[Unsmoothed Maximum Likelihood-based Training Algorithm]]. | ||
* <B>See:</B> [[Maximum Likelihood Estimation Algorithm]], [[Penalized Estimation Algorithm]], [[Normalized Estimation Algorithm]], [[Penalized Regression]]. | * <B>See:</B> [[Maximum Likelihood Estimation Algorithm]], [[Penalized Estimation Algorithm]], [[Normalized Estimation Algorithm]], [[Penalized Regression]]. | ||
Latest revision as of 06:54, 7 January 2023
A Penalized Maximum Likelihood Estimation Algorithm is a Maximum Likelihood Estimation Algorithm that ...
- …
- Counter-Example(s):
- See: Maximum Likelihood Estimation Algorithm, Penalized Estimation Algorithm, Normalized Estimation Algorithm, Penalized Regression.
References
2006
- (Vishwanathan et al., 2006) ⇒ S. V. N. Vishwanathan, Nicol N. Schraudolph, Mark W. Schmidt, and Kevin P. Murphy. (2006). “Accelerated Training of Conditional Random Fields with Stochastic Gradient Methods.” In: Proceedings of the 23rd International Conference on Machine learning (ICML-2006). doi:10.1145/1143844.1143966
- QUOTE: … Current training methods for CRFs (In this paper, “training” specifically means penalized maximum likelihood parameter estimation) include generalized iterative scaling (GIS), conjugate gradient (CG), and limited-memory BFGS. ...