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Maximum Entropy and Bayesian Methods

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Cover of 'Maximum Entropy and Bayesian Methods'

Table of Contents

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    Book Overview
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    Chapter 1 Reconstruction of the Probability Density Function Implicit in Option Prices from Incomplete and Noisy Data
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    Chapter 2 Model Selection and Parameter Estimation for Exponential Signals
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    Chapter 3 Hierarchical Bayesian Time Series Models
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    Chapter 4 Bayesian Time Series: Models and Computations for the Analysis of Time Series in the Physical Sciences
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    Chapter 5 Maxent, Mathematics, and Information Theory
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    Chapter 6 Bayesian Estimation of the Von Mises Concentration Parameter
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    Chapter 7 A Characterization of the Dirichlet Distribution with Application to Learning Bayesian Networks
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    Chapter 8 The Bootstrap is Inconsistent with Probability Theory
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    Chapter 9 Data-Driven Priors for Hyperparameters in Regularization
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    Chapter 10 Mixture Modeling to Incorporate Meaningful Constraints into Learning
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    Chapter 11 Maximum Entropy (Maxent) Method in Expert Systems and Intelligent Control: New Possibilities and Limitations
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    Chapter 12 The De Finetti Transform
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    Chapter 13 Continuum Models for Bayesian Image Matching
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    Chapter 14 Mechanical Models as Priors in Bayesian Tomographic Reconstruction
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    Chapter 15 The Bayes Inference Engine
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    Chapter 16 A Full Bayesian Approach for Inverse Problems
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    Chapter 17 Pixon-Based Multiresolution Image Reconstruction and Quantification of Image Information Content
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    Chapter 18 Bayesian Multimodal Evidence Computation by Adapti Tempering MCMC
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    Chapter 19 Bayesian Inference and the Analytic Continuation of Imaginary-Time Quantum Monte Carlo Data
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    Chapter 20 Spectral Properties from Quantum Monte Carlo Data: A Consistent Approach
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    Chapter 21 An Application of Maximum Entropy Method to Dynamical Correlation Functions at Zero Temperature
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    Chapter 22 Chebyshev Moment Problems: Maximum Entropy and Kernel Polynomial Methods
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    Chapter 23 Cluster Expansions and Iterative Scaling for Maximum Entropy Language Models
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    Chapter 24 A Maxent Tomography Method for Estimating Fish Densities in a Commercial Fishery
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    Chapter 25 Toward Optimal Observer Performance of Detection and Discrimination Tasks on Reconstructions from Sparse Data
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    Chapter 26 Entropies for Dissipative Fluids and Magnetofluids without Discretization
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    Chapter 27 On the Importance of α Marginalization in Maximum Entropy
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    Chapter 28 Quantum Mechanics as an Exotic Probability Theory
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    Chapter 29 Bayesian Parameter Estimation of Nuclear Fusion Confinement Time Scaling Laws
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    Chapter 30 Hierarchical Segmentation of Range and Color Image Based on Bayesian Decision Theory
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    Chapter 31 Priors on Measures
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    Chapter 32 Determining Whether Two Data Sets are from the Same Distribution
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    Chapter 33 Occam’s Razor for Parametric Families and Priors on the Space of Distributions
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    Chapter 34 Skin and Maximum Entropy: a Hidden Complicity ?
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    Chapter 35 Predicting the Accuracy of Bayes Classifiers
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    Chapter 36 Maximum Entropy Analysis of Genetic Algorithms
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    Chapter 37 Data Fusion in the Field of Non Destructive Testing
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    Chapter 38 Dual Statistical Mechanical Theory for Unsupervised and Supervised Learning
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    Chapter 39 Complex Sinusoid Analysis by Bayesian Deconvolution of the Discrete Fourier Transform
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    Chapter 40 Statistical Mechanics of Choice
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    Chapter 41 Rational Neural Models Based on Information Theory
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    Chapter 42 A New Entropy Measure with the Explicit Notion of Complexity
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    Chapter 43 Maximum Entropy States and Coherent Structures in Magnetohydrodynamics
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    Chapter 44 A Lognormal State of Knowledge
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    Chapter 45 Pixon-Based Multiresolution Image Reconstruction for Yohkoh’S Hard X-Ray Telescope
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    Chapter 46 Bayesian Methods for Interpreting Plutonium Urinalysis Data
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    Chapter 47 The Information Content of Sonar Echoes
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    Chapter 48 Objective Prior for Cosmological Parameters
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    Chapter 49 Meal Estimation: Acceptable-Likelihood Extensions of Maxent
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    Chapter 50 On Curve Fitting with Two-Dimensional Uncertainties
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    Chapter 51 Bayesian Inference in Search for the in Vivo T 2 Decay- Rate Distribution in Human Brain
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    Chapter 52 Bayesian Comparison of Fit Parameters Application to Time-Resolved X-Ray Spectroscopy
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    Chapter 53 Edge Entropy and Visual Complexity
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    Chapter 54 Maximum Entropy Tomography
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    Chapter 55 Bayesian Regularization of Some Seismic Operators
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    Chapter 56 Multimodality Bayesian Algorithm for Image Reconst: in Positron Emission Tomography
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    Chapter 57 Evidence Integrals
Attention for Chapter 9: Data-Driven Priors for Hyperparameters in Regularization
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Chapter title
Data-Driven Priors for Hyperparameters in Regularization
Chapter number 9
Book title
Maximum Entropy and Bayesian Methods
Published by
Springer, Dordrecht, January 1996
DOI 10.1007/978-94-011-5430-7_9
Book ISBNs
978-9-40-106284-8, 978-9-40-115430-7
Authors

Daniel Keren, Michael Werman, Keren, Daniel, Werman, Michael

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 50%
Student > Ph. D. Student 1 50%
Readers by discipline Count As %
Physics and Astronomy 1 50%
Unknown 1 50%