Penalized Maximum Likelihood Estimation Algorithm

A Penalized Maximum Likelihood Estimation Algorithm is a Maximum Likelihood Estimation Algorithm that ...

• • …
• Counter-Example(s):
  • an Unsmoothed Maximum Likelihood-based Training Algorithm.
• See: Maximum Likelihood Estimation Algorithm, Penalized Estimation Algorithm, Normalized Estimation Algorithm, Penalized Regression.

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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. ...

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