nlp:hmm
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Table of Contents
Hidden Markov Models
Basics
- HMMs vs CRFs: See Liang & Jordan 2008 - An Asymptotic Analysis of Generative, Discriminative, and Pseudolikelihood Estimators especially table 2, and summary slide 44 here
Applications in MT
Recent Advances
- Chiu & Rush 2020 - Scaling Hidden Markov Language Models Scaling the number of hidden states to 2^15 states, with exact inference.
- This paper shows that HMMs can be viewed as a special case of RNNs: Buys et al 2018 - Bridging HMMs and RNNs through Architectural Transformations
Tutorials and Introductions
Related Pages
nlp/hmm.1617272607.txt.gz · Last modified: 2023/06/15 07:36 (external edit)