[PDF] Top 20 Adaptive Language Modeling Using the Maximum Entropy Principle
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Adaptive Language Modeling Using the Maximum Entropy Principle
... ADAPTIVE LANGUAGE MODELING USING THE MAXIMUM ENTROPY PRINCIPLE A D A P T I V E L A N G U A G E M O D E L I N G U S I N G T H E M A X I M U M E N T R O P Y P R I N C I P L E Raymond Lau, Ronald Rosenfe[.] ... See full document
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A Maximum Entropy Approach for Semantic Language Modeling
... ME language model by measuring the model perplexity and the character-error rate in continuous speech ...n-gram language model is used as the baseline, while the ME language model proposed by Wu and ... See full document
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The Flow Resistance Factor Treated by the Maximum Entropy Principle
... Once developed the expression describing the distribution of velocities in flows, Chiu in 1993 also presented a new mathematical formulation to better model the shear factor, “ f ”, based on a more realistic velocity ... See full document
8
Maximum Entropy Modeling in Sparse Semantic Tagging
... Maximum Entropy (MaxEnt) principle has been success- fully applied in many classification and tagging tasks (Rat- naparkhi, 1996; ...MaxEnt modeling as the learning ... See full document
6
A Comparison of the Maximum Entropy Principle Across Biological Spatial Scales
... the maximum entropy principle, ranging from amino acids up to ...common language, this paper establishes a unified view over seemingly highly heterogeneous biological ... See full document
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Improvement of a Whole Sentence Maximum Entropy Language Model Using Grammatical Features
... Over the last decade, there has been an increas- ing interest in Stochastic Context-Free Grammars (SCFGs) for use in different tasks (K., 1979; Jelinek, 1991; Ney, 1992; Sakakibara, 1990). The reason for this can be ... See full document
8
A Fast Algorithm for Feature Selection in Conditional Maximum Entropy Modeling
... for language modeling tasks. Since ME models are optimized using their likelihood or likelihood gains as the criterion, it is important to establish the relationship between c 2 test score and the ... See full document
7
CRC Press Utility Based Learning from Data 2010 RETAiL EBook pdf
... the language of information theory and solved via maximum entropy (ME), mini- mum relative entropy (MRE), or minimum mutual information (MMI) meth- ...as entropy, relative ... See full document
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Predicting the Outcome of NBA Playoffs Based on Maximum Entropy Principle
... Maximum Entropy model is a good-performance adaptability and flexibility excellence statistical model, making probability estimates to the problem, which is suited to solve the problem of ...the ... See full document
13
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 measure of ... See full document
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An Introduction to the Non-Equilibrium Steady States of Maximum Entropy Spike Trains
... issue. Maximum entropy methods provide a principled way of addressing time irreversibility, which leverages powerful results and ideas from the3literature of non-equilibrium statistical ... See full document
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Tree Network Formation in Poisson Equation Models and the Implications for the Maximum Entropy Production Principle
... that entropy production in non-equilibrium open systems, where the continuous input and output of energy and materials are maintained, shows quite different aspects from those in isolated ...low entropy, ... See full document
14
Identification of Basic Phrases for Kazakh Language using Maximum Entropy Model
... Automatic phrase identification is an important task in natural language processing. A phrase is a group of words that work together. Phrase recognition is a grammatical unit agent between words and sentences in ... See full document
8
Confidence Interval Estimation for Precipitation Quantiles Based on Principle of Maximum Entropy
... the principle of maximum entropy (POME) has been used for a variety of applications in hydrology, the confidence intervals of the POME quantile estimators have not been ...samples. Using four ... See full document
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A Maximum Entropy Approach to Natural Language Processing
... The feature selection algorithm de- scribed in Section 4 calculated that if this constraint were imposed on the model, the log-likelihood w o u l d rise by approximately 0.019059 bits; s[r] ... See full document
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Domain Adaptation of Maximum Entropy Language Models
... The audio used for testing was segmented into parts of up to 20 seconds in length. Speaker diarization was applied using the LIUM SpkDiarization toolkit (Del´eglise et al., 2005). The CMU Sphinx 3.7 was used for ... See full document
6
Maximum Entropy and Maximum Likelihood Estimation for the Three Parameter Kappa Distribution
... . (5) As precisely mentioned, the maximization is usually accomplished via the method of Lagrange multipliers, such that the general solution form of the ME distribu- tions from maximizing the BGS entropy Equation ... See full document
5
Ant Possibilistic Fuzzy Clustered Forecasting on High Dimensional Data
... Efficient prediction of stock market for financial analysis not only serves for the short-tem investors but it is also an efficient means for long-term investors too. Principal Component Analysis was applied in [11] ... See full document
10
A Combined Entropy/Phase-Field Approach to Gravity
... Abstract: Terms related to gradients of scalar fields are introduced as scalar products into the formulation of entropy. A Lagrange density is then formulated by adding constraints based on known conservation ... See full document
13
A method to evaluate composite performance indices based on variance covariance matrix
... After we order the composite performance indices non-weighted or weighted we classify them using either the maximum entropy principle, either the maximum separation Chow breakpoint test.[r] ... See full document
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