[PDF] Top 20 Viterbi Training Improves Unsupervised Dependency Parsing
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Viterbi Training Improves Unsupervised Dependency Parsing
... We prove that learning can be error-prone even in cases when likelihood is an appropriate mea- sure of extrinsic performance and where global optimization is feasible. This is because a key challenge in ... See full document
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Unsupervised Dependency Parsing with Transferring Distribution via Parallel Guidance and Entropy Regularization
... on unsupervised grammar in- duction (Carroll and Charniak, 1992; Klein and Manning, 2004; Smith and Eisner, 2005; Cohen and Smith, 2009; Spitkovsky et ...as unsupervised methods require only unannotated ... See full document
12
Unsupervised Dependency Parsing: Let’s Use Supervised Parsers
... Unsupervised dependency parsing and its super- vised counterpart have many characteristics in com- mon: they take as input raw sentences, produce dependency structures as output, and often use ... See full document
11
Unsupervised Induction of Tree Substitution Grammars for Dependency Parsing
... Unfortunately finding the maximising parse tree for a string under our TSG-DMV model is intractable due to the inter-rule dependencies created by the PYP formulation. Previous work has used Monte Carlo techniques to ... See full document
10
Fast Unsupervised Dependency Parsing with Arc Standard Transitions
... Unsupervised dependency parsing is one of the most challenging tasks in natural lan- guages ...possible dependency trees from raw sentences without getting any aid from annotated ...mental ... See full document
9
Unsupervised Dependency Parsing using Reducibility and Fertility features
... Zabokrtsk´y (2012). Their statistics across languages are showed in Table 2. To make them useful, the necessary preprocessing steps must have been done. The texts were first automatically segmented and to- kenized 14 and ... See full document
6
Punctuation: Making a Point in Unsupervised Dependency Parsing
... We next re-examined the choices of constraints. Our full factorial analysis was similar, but signifi- cantly smaller, than Spitkovsky et al.’s (2010b): we excluded their larger-scale news and web data sets that are not ... See full document
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From Baby Steps to Leapfrog: How “Less is More” in Unsupervised Dependency Parsing
... Baby Steps: Global non-convex optimization is hard. We propose a meta-heuristic that takes the guesswork out of initializing local search. Begin- ning with an easy (convex) case, it slowly extends it to the fully complex ... See full document
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Combining Generative and Discriminative Approaches to Unsupervised Dependency Parsing via Dual Decomposition
... the training data with length ≤ 15 and tested our method on the testing data with length ≤ ...the training sentences and then used the parses to initialize the training of ...Convex-MST ... See full document
6
From ranked words to dependency trees: two stage unsupervised non projective dependency parsing
... Usually unsupervised dependency parsing tries to optimize the probability of a corpus by modifying the dependency model that was presumably used to generate the ...a dependency ... See full document
9
Semi Supervised Convex Training for Dependency Parsing
... class unsupervised and semi-supervised SVM learn- ing, which relaxes the original non-convex objective into a close convex approximation, thereby allowing a global solution to be ... See full document
9
Neutralizing Linguistically Problematic Annotations in Unsupervised Dependency Parsing Evaluation
... Headden et al. (2009) obtained the best reported results on WSJ10 by using a lexical extension of DMV. Gillenwater et al. (2010) used posterior reg- ularization to bias the training towards a small num- ber of ... See full document
10
Unsupervised Dependency Parsing without Gold Part of Speech Tags
... still unsupervised) clustering instead, ob- tained by executing standard sequence labeling tech- niques to introduce context-sensitivity into the origi- nal (independent) assignment or words to ...constrained ... See full document
10
Improving Unsupervised Dependency Parsing with Richer Contexts and Smoothing
... We trained on the standard Penn Treebank WSJ cor- pus (Marcus et al., 1993). Following Klein and Man- ning (2002), sentences longer than 10 words after removing punctuation are ignored. We refer to this variant as WSJ10. ... See full document
9
CRF Autoencoder for Unsupervised Dependency Parsing
... We evaluated our model on seven languages from the PASCAL Challenge on Grammar Induction (Gelling et al., 2012). We did not use the Arabic corpus because the number of training sentences with length ≤ 10 is less ... See full document
6
Unsupervised Neural Dependency Parsing
... There have been many more advanced learning al- gorithms of the DMV model beyond the basic EM algorithm. In the work of Cohen and Smith (2008), a logistic normal prior was used in the DMV model to capture the similarity ... See full document
9
Posterior Sparsity in Unsupervised Dependency Parsing
... EM training and the different sparsity inducing training methods for the ...each training method against EM training using the E-DMV model with the best setting found for ... See full document
36
Exploiting Reducibility in Unsupervised Dependency Parsing
... To investigate the impact of individual components of the model, we run the parser for all possible com- ponent combinations. We choose three languages along the scale of word order freedom: English (very rigid word ... See full document
11
Unsupervised Parsing for Generating Surface Based Relation Extraction Patterns
... the training set and ex- tracted shortest dependency path ...a dependency graph has been widely used as a representation of relation instance ... See full document
6
Concavity and Initialization for Unsupervised Dependency Parsing
... both training and ...When training on sentences of length ≤ 20 words (bold), the performance even rivals that of several more sophisticated models shown in the table, de- spite only using the DMV with a ... See full document
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