Methods of Maximum Entropy (MaxEnt)
Maximum Entropy Empirical Likelihood Methods Based on Bivariate Laplace Transforms and Moment Generating Functions
... MEEL methods are similar to properties of univariate MEEL methods as discussed by Luong [7] and will be further discussed in section ...likelihood methods as developed by Qin and Lawless [16] ...
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Iterative Scaling and Coordinate Descent Methods for Maximum Entropy Models
... ) methods are popular in training Maxent ...IS methods include general- ized iterative scaling ( GIS ) by Darroch and Ratcliff (1972), improved iterative scaling ( IIS ) by Della Pietra et ...CD ...
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Generalized Maximum Entropy Estimation
... This maximum entropy es- timation problem subject to moment constraints, also known as the principle of maximum entropy, is applicable to large classes of problems in natural and social ...
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Exponential Priors for Maximum Entropy Models
... cluster-based speedup (Goodman, 2001). We evaluated on test data using the standard language modeling mea- sure, perplexity, where lower scores are better. We tried five experiments: using Katz smoothing (a widely used ...
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Extraction of Information from Crowdsourcing: Experimental Test Employing Bayesian, Maximum Likelihood, and Maximum Entropy Methods
... maximizes entropy subject to the con- straints of prior ...of maximum entropy (PME) has a vast literature [19] [20], since it is widely used throughout the physical sciences and ...
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A Comparison of Algorithms for Maximum Entropy Parameter Estimation
... representations is not without cost. Even mod- est ME models can require considerable computa- tional resources and very large quantities of anno- tated training data in order to accurately estimate the modelâs ...
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Multitask Sparsity via Maximum Entropy Discrimination
... A maximum entropy discrimination (MED) framework is used to derive the multitask algorithm which involves only convex optimization problems that are straightforward to ...sparse methods are ...
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A Maximum Entropy Approach to Combining Word Alignments
... This paper presents a new approach to combining outputs of existing word align- ment systems. Each alignment link is rep- resented with a set of feature functions extracted from linguistic features and in- put ...
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Determination of Maximum Bayesian Entropy Probability Distribution
... determination methods of MEPD for univariate probability distribution functions are extended for multivariate cases via Bayesian ...numerical methods for determination of the maximum entropy ...
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Toward Tweets Normalization Using Maximum Entropy
... ear, are), which generates đ â 1 combinations. 3) Alteration strategy substitutes each character with all English alphabets (e.g. aer â ber, cer, der, eer, fer, ger, her, etc.), which generates 26đ combinations. 4) ...
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Maximum Entropy and Maximum Likelihood Estimation for the Three Parameter Kappa Distribution
... Various methods of estimation for this type of data include the L-moment, Moment, and Maximum Likelihood (ML) ...global maximum because it can de- pend upon the starting ...
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Entire Relaxation Path for Maximum Entropy Problems
... unknown distribution is distilled to a single scalar. We next describe in Sec. 4 a homotopy between the relaxation parameter and the distribution character- izing parameter. This formulation also reveals an aesthetic ...
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Sentiment Analysis Using SVM and Maximum Entropy
... are in most cases informal. On account that of the anomalistic nature of informal textual content, evaluation or processing of this sort of text is more often than not more difficult when compared to formal textual ...
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A Maximum Entropy Approach to Chinese Spelling Check
... Lexicon-based methods use dictionaries, which contain as much as possible language in- formation, such as word information, characters and words frequency information, encoding in- formation, part-of speech ...
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Subjectivity in Application of the Principle of Maximum Entropy
... Maximal consistency and rationality are indeed pri- mary goals of all our proposed methods of deterministic sampling. For complex models, such lean and custom- ized approaches are often required to obtain any ...
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Chinese Sentiment Analysis Using Maximum Entropy
... methods, such as NaĂŻve Bayes (NB), Maximum Entropy (ME), Support Vector Machine (SVM), unsupervised learning and etc. Hemnaath and Low (2010) propose sentiment analysis using Maximum ...
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Maximum Entropy Models for FrameNet Classification
... statistical methods for semantic ...a Maximum Entropy approach and by using previous tag information to find the high- est probability tag sequence for a given ...
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Maximum Entropy Reconstruction for Gas Dynamics
... Moment methods are closer in spirit to the familiar Navier-Stokes equations, which can actually be derived as a special case of a moment method [6], ...moment methods, described in detail in Chapter 5, is ...
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Maximum Entropy Discrimination Markov Networks
... generalized entropy optimization problem subject to expected margin constraints on the structured predictions, and under an arbitrary prior of feature coefficients; and we derive a general form of the solution to ...
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Statistical optimization for passive scalar transport: maximum entropy production versus maximum KolmogorovâSinai entropy
... gacity of the Zero Range Process is a passive scalar obeying a convectionâdiffusion equation, with advection velocity con- trolled by the probability to jump to the right or to the left, and diffusivity controlled by the ...
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