Витерби EM

method ID: viterbiem

Related Papers

Viterbi Training Improves Unsupervised Dependency Parsing

Authors: nan

Publication: TIPSTER (2010)

DOI: nan

We show that Viterbi (or “hard”) EM is well-suited to unsupervised grammar in- duction. It is more accurate than standard inside-outside re-estimation (classic EM), significantly faster, and simpler. Our ex- …...

42324

Unambiguity Regularization for Unsupervised Learning of Probabilistic Grammars

Authors: nan

Publication: TIPSTER (2012)

DOI: nan

We introduce a novel approach named unam- biguity regularization for unsupervised learn- ing of probabilistic natural language gram- mars. The approach is based on the observa- tion that natural language …...

44064

Nonconvex Global Optimization for Latent-Variable Models

Authors: nan

Publication: TIPSTER (2013)

DOI: nan

Many models in NLP involve latent vari- ables, such as unknown parses, tags, or alignments. Finding the optimal model pa- rameters is then usually a difficult noncon- vex optimization problem. …...

40246

Generalizing a Strongly Lexicalized Parser using Unlabeled Data

Authors: nan

Publication: TIPSTER (2014)

DOI: nan

Statistical parsers trained on labeled data suffer from sparsity, both grammatical and lexical. For parsers based on strongly lexicalized grammar formalisms (such as CCG, which has complex lexical cate- gories …...

43567

Unsupervised Discourse Constituency Parsing Using Viterbi EM

Authors: nan

Publication: TIPSTER (2020)

DOI: nan

AbstractIn this paper, we introduce an unsupervised discourse constituency parsing algorithm. We use Viterbi EM with a margin-based criterion to train a span-based discourse parser in an unsupervised manner. We …...

26943