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Results 1 - 10
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2,160,907
The Mathematics of Statistical Machine Translation: Parameter Estimation
- COMPUTATIONAL LINGUISTICS
, 1993
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A gentle tutorial on the EM algorithm and its application to parameter estimation for gaussian mixture and hidden markov models
, 1997
"... We describe the maximum-likelihood parameter estimation problem and how the Expectation-form of the EM algorithm as it is often given in the literature. We then develop the EM parameter estimation procedure for two applications: 1) finding the parameters of a mixture of Gaussian densities, and 2) fi ..."
Abstract
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Cited by 678 (4 self)
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We describe the maximum-likelihood parameter estimation problem and how the Expectation-form of the EM algorithm as it is often given in the literature. We then develop the EM parameter estimation procedure for two applications: 1) finding the parameters of a mixture of Gaussian densities, and 2
Parameter Estimation
, 2002
"... using measured steady-state values. 8. Parameter estimation without an explicit solution. 9. Demonstration of the procedure, and results. 1 ..."
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using measured steady-state values. 8. Parameter estimation without an explicit solution. 9. Demonstration of the procedure, and results. 1
A Comparison of Algorithms for Maximum Entropy Parameter Estimation
"... A comparison of algorithms for maximum entropy parameter estimation Conditional maximum entropy (ME) models provide a general purpose machine learning technique which has been successfully applied to fields as diverse as computer vision and econometrics, and which is used for a wide variety of class ..."
Abstract
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Cited by 285 (2 self)
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A comparison of algorithms for maximum entropy parameter estimation Conditional maximum entropy (ME) models provide a general purpose machine learning technique which has been successfully applied to fields as diverse as computer vision and econometrics, and which is used for a wide variety
for parameter estimation
, 1999
"... Abstract. The measurement of the intrinsic diffusivity of a semitransparent sample is investigated by means of the flash method. A precise analytical model of the combined transient conductive and radiative transfer (quadrupole formulation) is used for the parameter estimation problem. Maps of sensi ..."
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Abstract. The measurement of the intrinsic diffusivity of a semitransparent sample is investigated by means of the flash method. A precise analytical model of the combined transient conductive and radiative transfer (quadrupole formulation) is used for the parameter estimation problem. Maps
PARAMETER ESTIMATION by
, 2003
"... A method to identify synchronous generator parameters from on-line measurements is presented. Generator parameters are employed in the construction of models used in transient stability studies and other routine power engineering studies. These studies are critical for the operation of the power sys ..."
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internal temperature, magnetic saturation, and coupling between the generator and external systems. The method proposed in this dissertation estimates generator parameters at any operating level, taking into consideration the effect of saturation and other phenomena in the operation of the synchronous
Parameter estimation for text analysis
, 2004
"... Abstract. Presents parameter estimation methods common with discrete probability distributions, which is of particular interest in text modeling. Starting with maximum likelihood, a posteriori and Bayesian estimation, central concepts like conjugate distributions and Bayesian networks are reviewed. ..."
Abstract
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Cited by 117 (0 self)
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Abstract. Presents parameter estimation methods common with discrete probability distributions, which is of particular interest in text modeling. Starting with maximum likelihood, a posteriori and Bayesian estimation, central concepts like conjugate distributions and Bayesian networks are reviewed
Robust parameter estimation in computer vision
- SIAM Reviews
, 1999
"... Abstract. Estimation techniques in computer vision applications must estimate accurate model parameters despite small-scale noise in the data, occasional large-scale measurement errors (outliers), and measurements from multiple populations in the same data set. Increasingly, robust estimation techni ..."
Abstract
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Cited by 162 (10 self)
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Abstract. Estimation techniques in computer vision applications must estimate accurate model parameters despite small-scale noise in the data, occasional large-scale measurement errors (outliers), and measurements from multiple populations in the same data set. Increasingly, robust estimation
Calibration as Parameter Estimation in Sensor Networks
, 2002
"... We describe an ad-hoc localization system for sensor networks and explain why traditional calibration methods are inadequate for this system. Building upon previous work, we frame calibration as a parameter estimation problem; we parameterize each device and choose the values of those parameters tha ..."
Abstract
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Cited by 150 (7 self)
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We describe an ad-hoc localization system for sensor networks and explain why traditional calibration methods are inadequate for this system. Building upon previous work, we frame calibration as a parameter estimation problem; we parameterize each device and choose the values of those parameters
Parameter Estimation Techniques: A Tutorial with Application to Conic Fitting
, 1995
"... Almost all problems in computer vision are related in one form or another to the problem of estimating parameters from noisy data. In this tutorial, we present what is probably the most commonly used techniques for parameter estimation. These include linear least-squares (pseudo-inverse and eigen a ..."
Abstract
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Cited by 276 (8 self)
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Almost all problems in computer vision are related in one form or another to the problem of estimating parameters from noisy data. In this tutorial, we present what is probably the most commonly used techniques for parameter estimation. These include linear least-squares (pseudo-inverse and eigen
Results 1 - 10
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2,160,907
