log-linear model
Data driven learning of symbolic constraints for a log linear model in a phonological setting
... a log-linear model, so summing the weights of all violated constraints provides each candidate’s linear predictor, which is logit-transformed to a ...
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Novometric vs. Log-Linear Model: Intergenerational Occupational Mobility of White American Men
... Prior research 1 modeling intergenerational occupational mobility (professional and managerial=1; clerical and sales=2; craftsman=3; operatives and laborers=4; farmers=5) using several log-linear ...
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Adaptive Development Data Selection for Log linear Model in Statistical Machine Translation
... of log- linear SMT models, and presented principled methods for dynamically inferring test data de- pendent model parameters with development set ...of log-linear model ...
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Modeling the Non Substitutability of Multiword Expressions with Distributional Semantics and a Log Linear Model
... a log-linear ...best model can reach the same performance as the best ...a model with a performance that is significantly higher than the performance of the ...
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Log Linear Model for String Transformation Using Large Data Sets
... a log-linear (discriminative) model for string transformation, (2) an effective and accurate algorithm for model learning, and (3) an efficient algorithm for string ...The log ...
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Multinomial logit bias reduction via Poisson log linear model
... logit model (1) and the Poisson log-linear model (2) are both full expo- nential families, and so in either case the bias-reducing penalty of Firth (1993) to the likelihood is simply the ...
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On the Estimation of Parameters and Best Model Fits of Log Linear Model for Contingency Table
... [9] described the log linear model as a frame work for analyzing effects in contingency tables. That is, tables of frequencies formed by two or three variables of classification and he considered ...
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A Log Linear Model for Unsupervised Text Normalization
... a very challenging problem for unsupervised learn- ing. Perhaps it is for these reasons that the most suc- cessful systems are pipeline architectures that cob- ble together a diverse array of techniques and re- sources, ...
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Parameterization of Continuous Covariates in the Poisson Capture-Recapture Log Linear Model for Closed Populations
... Poisson log-linear model (LLM) can be used to model both the dependence and the heterogeneity (Schwarz and Seber, 1999) but, in presence of continuous covariates, the maximum likelihood ...
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Inflation Behavior in Top Sukuk Issuing Countries: Using a Bayesian Log-linear Model
... a model to study the effect of Sukuk issuance on the inflation rate of top Sukuk issuing Islamic economies at ...regression model is applied which contains key supply and demand side factors in addition to ...
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Conditional Independence test for categorical data using Poisson log linear model
... The R package pcalg contains two functions, gSquareBin when all the variables are binary and gSquareDis for all other cases. In addition, the function disCItest which is a wrapper of gSquareDis will also be examined. The ...
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Locally Training the Log Linear Model for SMT
... translation model and can be seen as the adaptation of trans- lation ...translation model which needs to run GIZA++ and it incrementally trains lo- cal weights, our method can be applied for online ...
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A Virtual Manipulative for Learning Log Linear Models
... conditional log-linear model (Ratnaparkhi, ...to model the proba- bility of all rules given their left-hand sides, based on features that consider attributes of the nonter- ...
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Parsing the WSJ Using CCG and Log Linear Models
... The packed charts perform a number of roles: they are a compact representation of a very large num- ber of CCG derivations; they allow recovery of the highest scoring parse or dependency structure with- out enumerating ...
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Unsupervised Morphological Segmentation with Log Linear Models
... existing model-based systems for unsupervised morphological segmentation use directed generative models, making it dif- ficult to leverage arbitrary overlapping fea- tures that are potentially helpful to ...first ...
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The Cunei Machine Translation Platform for WMT ’10
... non-parametric model that assesses the relevance of each translation ...to model a phrase pair by computing relative frequencies over the collection of transla- tion ...This model for the phrase pair ...
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A Log Linear Block Transliteration Model based on Bi Stream HMMs
... Overall, our proposed feature functions cover rela- tively different aspects for transliteration blocks: the block level length relevance probability in Eqn. 5, lexical translation equivalence, and positions’ distortion ...
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Unsupervised Topic Modeling for Short Texts Using Distributed Representations of Words
... topic model that uses soft clustering over distributed representations of ...a log-linear model and we model the low-dimensional seman- tic vector space represented by the dense word ...
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Joint Inference for Bilingual Semantic Role Labeling
... inference model. Our model prefers the bilin- gual SRL result that is not only reasonable on each side of bitext, but also has more consis- tent argument structures between two ...a log-linear ...
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Perceptron Reranking for CCG Realization
... n-gram log probability of each can- didate realization as a feature in their log-linear model yielded a substantial boost in ranking per- formance; on the Penn Treebank (PTB), however, ...
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