maximum entropy models
A Joint Syntactic and Semantic Dependency Parsing System based on Maximum Entropy Models
... 2009 shared task is presented. The system is com- posed of three components: a syntactic dependency parser, a predicate classifier and a semantic parser. The first-order MSTParser is used as our syntactic dependency ...
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Simple Maximum Entropy Models for Multilingual Coreference Resolution
... Ontonotes. Maximum entropy models are used for our system as classifiers to deter- mine the coreference relationship between ev- ery two mentions (usually noun phrases and pronouns) in each ...
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Maximum Entropy Models for FrameNet Classification
... The development of FrameNet, a large database of semantically annotated sen- tences, has primed research into statistical methods for semantic tagging. We ad- vance previous work by adopting a Maximum ...
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Iterative Scaling and Coordinate Descent Methods for Maximum Entropy Models
... Maxent models to part of speech (POS) tagging and chunking ...learning models such as CRF (Conditional Random Fields) may outperform Maxent for these NLP ...learning models as the focus of this paper ...
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Discriminative Training and Maximum Entropy Models for Statistical Machine Translation
... train models for natural language un- derstanding rather than natural language ...alignment models, which have been shown to be a very powerful component for statistical machine translation ...
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FrameNet based Semantic Parsing using Maximum Entropy Models
... We train the ME models using the GIS algorithm (Darroch and Ratcliff, 1972) as implemented in the YASMET ME package (Och, 2002). For testing, we use the YASMET MEtagger (Bender et al. 2003) to perform the Viterbi ...
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Using Maximum Entropy Models to Discriminate between Similar Languages and Varieties
... language models and white (or black) lists, echo Gold’s information presentation ...n-grams models, which were also used by Dunning (1994) and Cavnar and Trenkle ...
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Unsupervised training of maximum entropy models for lexical selection in rule based machine translation
... The approaches by Berger et al. (1996) and by Mareˇ cek et al. (2010) cited above both take advan- tage of a parallel corpus to collect counts of con- texts and translations in order to train maximum- ...
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Parsing Syntactic and Semantic Dependencies with Two Single Stage Maximum Entropy Models
... The joint parsing of syntactic and semantic depen- dencies introduced by the shared task of CoNLL- 08 is more complicated than syntactic dependency parsing or semantic role labeling alone (Surdeanu et al., 2008). For ...
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Evaluation and Extension of Maximum Entropy Models with Inequality Constraints
... This optimization can be solved using algo- rithms such as the GIS algorithm (Darroch and Rat- cliff, 1972) and the IIS algorithm (Pietra et al., 1997). In addition, gradient-based algorithms can be applied since the ...
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Exponential Priors for Maximum Entropy Models
... describe, models satisfying Equa- tion 2 will have the property that, for each λ i , either a) λ i = 0 and expected[i] ≥ observed[i] − α i or b) expected[i] = observed[i] − α i ...
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The Calibration of Some Stochastic Volatility Models Used in Mathematical Finance
... the maximum probability of rejecting the null hypothesis when the null hypothesis is ...volatility models are considered it is necessary to build ad hoc statistical ...
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Mathematical and computational modeling in biology at multiple scales
... the maximum entropy principle as an inference tool for the study of phenomena at different scales, from gene evolution and gene networks to protein-drug molecular interactions, followed with a survey of the ...
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Generalized Maximum Entropy Estimation
... the maximum entropy subject to finite moment constraints can be approximated by using duality of convex ...the maximum entropy principle with generalized regularization measures, that as a ...
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Maximum Entropy Translation Model in Dependency Based MT Framework
... The idea of using maximum entropy for con- structing forward translation models is not new. It naturally allows to make use of various features potentially important for correct choice of target- ...
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Tree Network Formation in Poisson Equation Models and the Implications for the Maximum Entropy Production Principle
... mathematical models to simulate tree network formation using the Poisson equation and the Finite Difference Method ...of Maximum Entropy Produc- tion ...when entropy production is maximized, ...
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Statistical optimization for passive scalar transport: maximum entropy production versus maximum Kolmogorov–Sinai entropy
... depends on the parameters of the system namely on the de- gree of non-equilibrium. This fact can be the explanation for two well-known issues in climate/weather modelling. First, it explains that, when downgrading or ...
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Maximum entropy production: can it be used to constrain conceptual hydrological models?
... The question is thus: does nature acts in a similar way, where a fast process considers a slow process as constant and where processes that are not (or to a minimum) influenced by other processes see the other processes ...
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Chinese Chunking Based on Maximum Entropy Markov Models
... on maximum entropy Markov ...chunking models are ...and maximum entropy chunking ...two models, we propose a maximum entropy Markov chunking model that combines the ...
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On the complexity of computing maximum entropy for Markovian Models
... G is the set of states which are recurrent in some implementation of I. Evidently this is a formula in the first-order theory of ordered real fields extended with exponential functions ( R , +, −, ·, e x , 0, 1, ≤). The ...
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