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ml:em_algorithm [2021/03/30 10:28] – created jmflanigml:em_algorithm [2023/06/15 07:36] (current) – external edit 127.0.0.1
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 ====== EM Algorithm ====== ====== EM Algorithm ======
 +
 +===== Older Papers =====
 +  * Hard EM (also called "Viterbi training" or "sparse EM")
 +    * [[https://www.cs.toronto.edu/~hinton/absps/emk.pdf|Neal & Hinton 1998 - A view of the EM algorithm that justifies incremental, sparse, and other variants]] Calls it "sparse EM"
 +    * [[https://aclanthology.org/W10-2902.pdf|Spitkovsky et al 2010 - Viterbi Training Improves Unsupervised Dependency Parsing]]
 +    * [[https://aclanthology.org/P10-1152.pdf|Cohen & Smith 2010 - Viterbi Training for PCFGs: Hardness Results and Competitiveness of Uniform Initialization]]
  
 ===== Recent Papers ===== ===== Recent Papers =====
-  * [[https://www.aclweb.org/anthology/2020.tacl-1.15.pdf|Nishida & Nakayama - Unsupervised discourse constituency parsing using Viterbi EM]] +  * [[https://www.aclweb.org/anthology/2020.tacl-1.15.pdf|Nishida & Nakayama 2020 - Unsupervised discourse constituency parsing using Viterbi EM]] 
 +  * [[https://arxiv.org/pdf/2209.01232.pdf|Wang et al 2022 - Elaboration-Generating Commonsense Question Answering at Scale]] Uses an EM-style algorithm to train the background knowledge generator 
 + 
 +===== Related Pages ===== 
 +  * [[nlp:Unsupervised Methods]]
  
ml/em_algorithm.1617100114.txt.gz · Last modified: 2023/06/15 07:36 (external edit)

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