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Maximum Entropy Methods

abbreviation(s): MEM
definition: Maximum entropy methods are techniques for the estimation of probability distributions that pick the "most uniform" distribution compatible with the observed statistics. The maximum entropy formulation has a unique solution which can be found by iterative scaling algorithms. Maximum entropy models have been applied to NLP-related task like text segmentation and classification, language modeling, part-of-speech tagging, parsing, and machine translation.
related person(s):
  • Stefan Riezler
  • Roni Rosenfeld
  • John D. Lafferty
  • Adam L. Berger
  • Rob Malouf
  • Adwait Ratnaparkhi
  • Mark Johnson
  • Steven Paul Abney
related system(s) / resource(s):
  • Mnemonic Predictive Modeling Toolkit